Docstoc

A DCT based Algorithm for Blocking Artifact Reduction from DCT Coded Images

Document Sample
A DCT based Algorithm for Blocking Artifact Reduction from DCT Coded Images Powered By Docstoc
					            A DCT based Algorithm for Blocking Artifact
                Reduction from DCT Coded Images
                                                 Vinay Kumar Srivastava
 Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology, Allahabad, India
                                         E-mail: vksrivastaval2@rediffmail.com

    Abstract- The edge component causes the high frequency                                       local statistics of the image. In these algorithms, the
components in the transformed domain. Thus, examining the                                        classification of image areas is used to capture the non-
discrete cosine transform (DCT) coefficients of the block itself
can identify the monotone blocks. Moreover, the artificial
discontinuities in monotone area due to blocking artifacts also
                                                                                                 stationary behavior  of the image. Classification        Si
                                                                                                                                                        based on
                                                                                                 available edge information extracted from the received blocky
cause the high frequency components in DCT domain. Thus, these                                   image. Hence the performance of space-variant or adaptive
discontinuities are reflected as high frequency components in the                                filtering scheme degrades. Furthermore, the need of strong
DCT of concatenated block of two or more neighboring monotone                                    filter in monotone area and weak directional filter in edge area
blocks. It is also found that there exists a relationship between the
DCT coefficient of two monotone blocks and that of concatenated                                  makes it complex In references [7]-[15], the blockig artfacts
block. The DCT coefficients due to blocking artifacts are present                                are reduced by processing the image in DCT domain itself. The
in the concatenated block but not in individual block. Therefore,                                DCT domain algorithms are efficient since the signal need not
from the relationship between the DCT coefficients of monotone                                   be compressed or decompressed. Recovery of accuracy loss in
block of different sizes we can detect the high frequency                                        DCT coefficient by discontinuity criterion is another method
components due to blocking artifacts and thus we can eliminate                                   that can reduce these artifacts efficiently in monotone area.
them to reduce the blocking artifacts.
                                                                                                 Jeon and Jeong [8] proposed a method for post-processing that
Keywords: Post-processing, Blocking artifacts, DCT, DCT-domain                                   gives minimum discontinuity of pixel values over block
processing, Block transform coding.                                                              boundaries by compensating the loss of a coefficient's
                              I.     INTRODUCTION                                                accuracy in the transform domain. In [9], Hsia et al. proposed
  In block discrete cosine transform (BDCT) based image                                          transform-domain algorithm to effectively classify the
compression the blocking artifacts are main cause of                                            characteristics of blocks and estimate the strength of the blocky
degradation, especially at higher compression ratio. This is the                                effect. An adaptive fmite impulse response filter to effectively
                                                                                                remove the blocky effect also proposed. In [10], Peak et al.
main drawback of BDCT based image compression schemes
and thus wavelet based image compression is used in new                                         proposed a method in which two adjacent homogeneous blocks
                                 -..               .
standard JPEG 2000. Most of the image compression standards ..                                 ~~~from block boundar are found and the local frequency
                                                                                                                      ry                                  qu y
(e.g., JPEG, MPEG, and H.263) use BDCT in their image                                           characteristics in the homogeneous block are examined
compression scheme due to its excellent energy compaction                                       through DCT. Then, relation between the DCT coefficients of
and de-correlation properties. DCT is used to exploit the spatial                               two homogeneous blocks of different sizes is derived. By
correlation for image compression. In BDCT based image                                          considering this information the high-frequency components
compression, the image degradation becomes visible when                                         mainly caused by the blocking artifact are detected.
          'psoriexceeds certain level. hs erdhn
compression ratio ecescranlvl These degradations                                                   Recently, Chen et al. [11] introduced a DCT-domain post-
manifest themselves as blocking artifacts due to the rigid block                                filtering approach to reduce blocking artifacts, where the post-
partitioning of the image and ringing noise around edges due to                                 filter made use of the DCT coefficients of shifted blocks in
coarse quantization. Both effects are visually annoying and                                     order to obtain a close correlation between the DCT
have substantial impact on the subjective quality of image. At                                  coefficients at the same frequency. In [12], Chang and
higher compression ratios, since very few coefficients are                                      Messerschmitt, proposed algorithms to manipulate compressed
encoded and each coefficient must be represented at a very                                      video in the transform domain. In [13], a method for efficiently
                                                                                                assessing, and subsequently reducing, the severity of blocking
visible,
visible.                                                                                        artifacts in compressed image bitstreams is proposed. In the
  Linear, space-invariant filtering is inadequate to remove                                     algorithm, blocking artifacts are modeled as 2-D step
these artifacts whereas iterative methods such as projections                                   functions. A fast DCT-domain algorithm extracts all
onto convex sets (POCS) have greater computational                                              parameters needed to detect and estimate the blocking artifacts,
                                            c
                               post-processingpxySellrh                   [1]-       av e       by exploiting several blockiness, ofnovelhuman vision method
                                                                                                Using the estimate of properties a the DCT-domain system.
been proposed to reduce blocking artifacts Of blocki coding    1
system. Out of these algorithms space-variant / adaptive                                        is then developed which adaptively reduces detected blocking
filtering techniques are more attractive as they try to exploit the                             ariacs Lu an Wad[4 rpsdatcnqe hc
                                                                                                preserved the edge and texture information. This adaptive


        1-4244-0726-5/06/$20.OO '2006 IEEE                                                2815

 Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.
approach performs blocking artifact reduction in both the DCT                                     The DCT of concatenated row can be expressed as:
and spatial domains. For smooth regions, the continuity of
original pixel levels in the same block and the correlation                                                        1                           k /2
between the neighboring blocks is used to reduce the                                                                   2
discontinuity of the pixels across the boundaries. For texture
and edge regions an edge-preserving smoothing filter is                                                                                                   for   k=0,2,4,
applied. Zhao et al. [15], proposed a DCT domain deblocking
technique by shifting the blocks successively in horizontal and                                                                                     F           1
vertical directions, respectively, and simultaneously shrinking                                  W(k)                                        )cos7(2n + 1)k
                                                                                                                                              c
the undesired high frequency DCT coefficients.                                                                     a(k) N -L                              4             +
   This paper is organized as follows. In Section II, the                                                                                           1)                  _
algorithm to reduce blocking artifacts is described. Simulation                                                            2             /1)              v(n)sin ;T(2n + I)k
results are presented in Section III. Finally, conclusions are                                                                                                      L       4N
given in Section IV.
                            11. PROPOSED SCHEME                                                                                                           for       k = 1,3,5,...
                                                                                                                    (4)
   Blocking artifacts are mainly due to independent coding of
                                                        From the above equation (4) it is clear that the even
                                                     numbered (2kth) DCT coefficient of W depends only on the kth
different blocks. The edge components of image cause the high
frequency components in the transformed domain. Thus,          DCT      of Uand Vwhereas the odd numbered DCT     coefficients
examining the DCT coefficients of the block itself can identify
                                                     coefficients of W are expressed as a weighted sum of u(n) and
the monotone or edge block. The artificial discontinuities in
                                                     v(n). Thus, only the odd numbered DCT coefficients of W are
monotone area are due to blocking artifacts. These   affected by the artificial discontinuities in the block. Assuming
discontinuities also cause the high frequency components. In
                                                     that the original image is highly correlated and the global
the proposed algorithm two horizontally adjacent blocks of size
                                                     frequency characteristics in two adjacent blocks should be
N x N are concatenated to make a new block of size 2N x N.
                                                     similar to the local frequency characteristics in each block.
The discontinuities due to blocking artifacts are reflected as
                                                     Thus, the high-frequency components in the global
high frequency components in the DCT of concatenated block
                                                     characteristics of a decoded image, which are not found in the
of two or more neighboring monotone blocks. It is also found
                                                     local ones, can be considered as a result from the blocking
that there exists a relationship between the DCT coefficient of
                                                     artifact. Here, N-point DCT will be employed to obtain the
two monotone blocks and that of concatenated block. The DCT
                                                     local characteristics, and 2N-point DCT to obtain the global
coefficients due to blocking artifacts are present in the
                                                     ones. The relation between N-point and 2N-point DCT
concatenated block but not in individual block. Therefore, from
                                                     coefficients is used to detect the undesired high frequency
the relationship between the DCT coefficients of monotone
                                                     components, mainly caused by the blocking artifact. If the
block of different sizes we can detect the high frequency
                                                     original image is highly correlated so that the block
components due to blocking artifacts and thus we can eliminate
                                                     discontinuities are invisible, then the odd-numbered DCT
them to reduce the blocking artifacts. The algorithm is also
                                                     coefficients of W of the original image can be approximated by
applied to vertically adjacent blocks to reduce the artificial
                                                     interpolating adjacent even-numbered coefficients. Thus, from
discontinuities due to blocking artifacts in horizontal direction.
                                                     equation (4), the nonzero DCT coefficients of W are kept
   To find the relationship between N x N DCT and 2N x N
                                                     within the range two times larger than those of U and V. In the
DCT we extend the results obtained in [10]. The two adjacent
                                                     decoded image, if nonzero coefficients of W occur at higher
rows u(n) and v(n) are concatenated as w(n) and their DCT are
                                                     locations than twice the highest nonzero valued location of U
given by U(k), V(k) and W(k), respectively, as       and V then those coefficients are believed to be the results of
                      N-1        Fz(2n + l)k 1artificial discontinuities due to the blocking artifact. Thus,
        U(k) = a(k) L u(n) cos                   (1) actual nonzero coefficients due to signal are kept within the
                      n=O        _    2N _J          range two times larger than those of U and V.
                                                        For concatenated 2D blocks, actual nonzero DCT
        V(k) = r(k) L v(n) cosl             1    (2) coefficients are present within the range two times larger than
                      n=O        L 2N j              those of DCT coefficients of constituent block for all rows and
                                                     column. The coefficients beyond this range are the coefficients
              1        2N-1         FT(2n + 1)k      due to the blocking artifacts. In proposed algorithm, the DCT
    W(k)          a(k)      w(n)cos  ,           (3) coefficients in the first row and first column that are beyond
                                                     this range are eliminated. Only first row and first column are
                1                      2             selected because of the effect of vertical and horizontal
where oc(k) =|for k=0 and c~(k) =| for other values. discontinuities which has greater values in these locations. This
                N                      N             algorithm has low computational complexity, as no filterinLg is


                                                                                          2816

 Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.
required. The availability of fast algorithm for DCT corresponding index of concatenated block will increase and
computation makes this algorithm suitable for low bit rate the edges will not be blurred by elimination.
coding applications. The selection of first row and first column A. Corner Outliers Detection and Replacement
for elimination further reduces the computation time.              As discussed in [4], corner outliers are visible at the cross
Following are the main steps of proposed Block Boundary                of MxM blo
   Dicntnite Reuto Aloitm                                        point oor Mblck when the corner pixel of one block iS very
                                                                 large very small as compared to corner pixels of the
   Step 1: Identification of block as monotone block: Actual neighboring blocks. The corner outliers detection and
edges are blurred due to elimination of high frequency replacement algorithm [4] is used here.
components. To protect the actual edges, this algorithm
requires the identification of monotone blocks. In proposed
algorithm, we selected only first row and first column for                      A3 A2 B2 B3
elimination of some DCT coefficients. Therefore, this step can                  Al A B B,
be bypassed. In fact, in implementation of this algorithm, this                        -                     Block               -C-D-D<I
step is ignored because this algorithm doesn't produce much                     Cl C D                    boundary
undesirable blur as discussed above.                                            C3 C2 D2 D3
   Step 2: Joining two horizontally adjacent monotone
blocks and transforming the concatenated block in DCT            In this algorithm, each corner pixel is compared with its
domain: The two horizontally adjacent monotone blocks of neighbors to detect the corner outliers whereas to reduce this
size M x M are concatenated into one block of size 2M x M. effect the corner A and its neighbors (A1 and A2) are replaced
The DCT coefficients due blocking artifacts are present in the by its weighted average as given below:
concatenated block but not in individual block. The 2M x M
DCT of concatenated block gives the global characteristics.                                                            A = (4A + B + C + 2D + 4)/8
The value of M is taken as 8 for this simulation.                                                                      A - (A + 3A + 2)/4                              (5)
  Step 3: Finding the maximum non-zero valued index for                                                                A2 = (A' + 3A2 + 2) / 4
the concatenated block for elimination of DCT coefficients
corresponding to blocking artifacts: The global frequency                                                                             III. RESULTS
characteristics in two adjacent blocks are similar to local ones
in each block. This concept is used in identifying and                                           DIn this section results
                                                                                                                        of the proposed Block Boundary
 elimiatin th coffiiet du to blckn artiat the th
                                           eliminating in                                        Discontinuities Reduction
                                                                                      cefcetdLenna image are presented. algorithm applied on 256 x with
                                                                                                                        The algorithm is implemented
                                                                                                                                                     256
concatenated block. For two blocks, the index of first row and
first column are found by checking them for non-zero values                                      M\ATLAB. To get blocky . image. at. different quality factors,'.a
                                                                                                     .         .
greater than a threshold. The practical value of threshold is                                    block imaGgorocess
                                                                                                 blocky image S post-processed by the proposedalgorithm.
                                                                                                                                       proposed algorithm.
found during simulation. The maximum non-zero valued index
for any row or column of a block is defined as the location                                      Various results are given in Table I and II Various quality
beyond which all the DCT coefficients are greater than a                                         measures are calculated to see the performances of the
tresod For cocteae blck it is fon tha th
  thehod Fo cocteae blck it is fon tha the                                                       algorithms. The results of the algorithm are compared with
                                                                                                 baseline JPEG like Dmg decoded image. Peak signal to noise
coefficients beyond the twice the maximum of these index                                         basin JPEG likeDCT
                                                                                                 r
values in respective dimension for two individual blocks, are
zero. Thus, in concatenated block if the coefficient beyond this
index exists then it is assumed that they are due to blocking                                                  PSNR In dB =M10 g10
                                                                                                                                         r                i2552
                                                                                                                                                          6
                                                                                                                                                         (6)
                                                                                                                                             SE
artifacts and thus they are eliminated. In this algorithm, the
selection of first row and first column for elimination further                                    where 255 is the peak signal for 8 bit PCM. MSE is mean
reduces the computation time.                                                                    square error given by:
                                                                                                                       MSE= 1I -2 Y a
                                                                                                                                N-1 N-1                    ~   \
  Step 4: Repeat the above all steps for vertically adjacent                                                                                                           (7)
blocks: To reduce the artificial discontinuities due to blocking                                                           N2 L i=o j=0                            j
artifacts in the horizontal direction, all the steps of the
algorithm are repeated by combining the two vertically                                              where 4, and 4, are the pixel values at position (i, j) of
adjacent blocks.                                                                                 original and decoded image respectively.
  Another reason for ignoring the first step is that the index of                                   Subjective quality of an image depends on the properties of
concatenated block is dependent on the maximum value of the                                      human visual system (HVS), as discontinuities are more visible
index in two dimensions for the two individual blocks,                                           in monotone or slowly varying areas. Therefore, the PSNR is
Therefore, if one or both blocks are edge block then the                                         only the rough indicator of image quality and does not reflect
                                                                                                 the blocking artifacts. A new discontinuity measure is defined.


                                                                                          2817


 Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.
                        -
                                                  (a)                                                                                       (b)




                                                  (c)                                                                                       (d)




                                m                                                                                     m~ ~ ~ ~ ~ ~ ~ ~ ~ ~
                                                   (e)                                                                                      (f)
Fig.1: Post-processed Lenna image compressed at 0.25386 bits/pixel by various algorithms. (a) DCT decoded. (b) Proposed Block Boundary Discontinuities
Reduction Algorithm (c) With corner outliers reduction. (d), (e) and (f) gives corresponding results for Lenna image compressed at 0.30483.



                                                                                           2818

  Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.
                                                                                                                                                                                                                                                                                                                     .. .
                                                                                                                                                                                                                                                                                                                     .... ..

                                                                    ................... ....




                                                                                                   .......
                                                                                                   ....................




                                                                                                                                                     ................




                                          ......................................................................................................................




                                                                                                                                                                                                                                                                                            ...
                                                                                                                                                                                                                                                                                        .......
                                                                                                                                                                                                                                                                                      ......................




                                    (a)                                                                                                                                                                      (b)                                                                                               (c)
Fig.2: Enlarged photographs of details of deblocked Lenna image compressed at 0.25386 bits/pixel by various algorithms. (a) DCT decoded. (b) Proposed Block
Boundary Discontinuities Reduction Algorithm (c) With corner outliers reduction.




                                 ..........................................




                                                              ......................................................




                                                                                                                                                      .................................
                                                                                                                                                                                                              .....
                                                                                                                                                                                                              .........
                                                                                                                                                                                          .....................
                                                                                                                                                                                                                  .
                                                                                                                                                                                                                  ..      ........................




                                                                                                                                                                                                                                         ............................................................




                                                                                                                                            .................................
                                                                                                                                                                                                                                                                            ......
                                                                                                                                                                                                                                                                            ...........
                                                                                                                                                                                                                                                                ................................




  Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.
                                       TABLE I                                                   Although this algorithm look very simple but this algorithm is
   PERFORMANCE OF THE PROPOSED ALGORITHMS ON COMPRESSED LENNA                                          g         g              ry                        ag
                                                                                                 able to reduce blockig artifacts significantly without much
 IMAGE: COMPARISON OF PSNR (IN dB) OBTAINED BY VARIOUS ALGORITHMS
                                                                                                                    c                                s




                                        Post- processed by                                       computational complexity. The performance of this algorithm
    Compression                          Block Boundary               With Corner                is better at high compression ratios; therefore it is suitable for
                      DCT                                                                        low bit rate videoin coding applications. The DCTartifacts
   in bits per pixel Decoded
         (bpp)
                                          Discontinuities
                                            Reduction                   Outliers
                                                                       Reduction                 algorithm proposed this paper reduces the blocking based
                                            Algorithm                                            by eliminating some DCT coefficients of concatenated block of
        0.30483           26.379               26.647                    2.5739                  two adjacent blocks. This algorithm has low computational
        0.34958           27.338               27.550                    27.621                  complexity, as no filtering is required. The availability of fast
        0.37165           27.701               27.915                    27.979                  algorithm for DCT computation makes this algorithm suitable
        0.40969           28.337               28.510                    28.537                  for low bit rate coding applications. The selection of first row
        0.44725           28.844               29.004                    29.022                  and first column for elimination further reduces the
        0.48188           29.268               29.386                    29.385
        0.51541           29.636               29.737                    29.720                  computation time. The results show that this algorithm
        0.54321           29.936               30.026                    30.005                  provides very good performance with minimum computational
                                                                                                 complexity.
                            TABLE II                                                                                                  REFERENCES
   PERFORMANCE OF THE PROPOSED ALGORITHMS ON COMPRESSED LENNA
IMAGE: COMPARISON OF BPSNR (IN dB) OBTAINED BY VARIOUS ALGORITHMS                                [1]    B. Ramamurthi and A. Gersho, "Non-linear space-variant post processing
                                                                                                        of block coded image", IEEE Trans. Acoustics, Speech and Signal
                                                Post-processed                                          Processing, vol. ASSP-34, no. 5, pp. 1258-1268, Oct. 1986.
 Compression in                                 by Block       With Corner                       [2]    C.J. Kuo and R.J. Hsieh, "Adaptive post-processor for block encoded
                                                Boundary                                                images", IEEE Trans. Circuit Syst. Video Technol., vol. 5, no. 4, pp. 298-
 (bltsperp)
 bits per pixel
 (bPP)
           xe           DCT Decoded
                        DCTDeoded             |Discontinuities Outliers
                                                Reduction Reduction     Reduti|n304,
                                                                                [3]
                                                                                                              Aug. 1995.
                                                                                                         Y.L. Lee, H.C. Kim, and H.W. Park, "Blocking effect reduction of JPEG
                                                Algorithm                                               images by signal adaptive filter ring", IEEE Trans. on Image Processing,
 0.25386                15.930                  16.523                  16.773                          vol. 7, no. 2, pp. 229-234, Feb. 1998.
 0.30483                17.358                  17.838                  18.033                   [4]     H. W. Park and Y. L. Lee, "A post-processing method for reducing
 0.34958                18.324                  18.688                  18.837                          quantization effects in low bit-rate moving picture coding", IEEE Trans.
 0.37165                18.748                  19.125                  19.259                          Circuit Syst. Video Technol., vol. 9, no. 1, pp. 161-171, Feb. 1999.
 0.40969                19.438                  19.738                  19.795                   [5]     S.D. Kim, J. Yi, H.M. Kim, and J.B. Ra, "A deblocking filter with two
 0.44725                19.971                  20.265                  20.305                          separate modes in block based video coding", IEEE Trans. Circuit Syst.
 0.48188                20.528                  20.747                  20.746                          Video Technol., vol. 9, no. 1, pp. 156-160, Feb. 1999.
 0.51541                20.946                  21.140                  21.103                   [6]    V.K. Srivastava and G.C. Ray, "Design of 2D-multiple Notch Filter and
 0.54321                21.246                  21.407                  21.361                          Its Application in Reducing Blocking Artifact from DCT Coded Image",
                                                                                                        in Proc. IEEE Int. Conf. Engineering in Medicine and Biology, Chicago
                                                                                                        2000, pp. 2829-2833, 23-28 July, 2000.
The block boundary PSNR (BPSNR) is defined in the same                                           [7] V.K. Srivastava, "Post-processing of DCT coded images", PhD
way as PSNR but only one pixel from both side of block                                                  dissertation, IIT Kanpur, India, Jan. 2001.
                                                                                                 [8] B. Jeon and J. Jeong, "Blocking artifacts reduction in image compression
boundary are considered for the calculation of MSE.                                                     with block boundary discontinuity criterion", IEEE Trans. Circuit Syst.
   The selective attenuation of AC component corresponding to                                           Video Technol., vol. 8, no. 3, pp. 345-357, June 1998.
block boundary discontinuities shows significant reduction in                                    [9] S.C. Hsia, J.F. Yang, and B.D. Liu, "Efficient postprocessor for blocky
blocking artifacts. Finally corner outliers detection and                                            effect removal based on transform characteristics", IEEE Trans on
                                                                                                        circuits and systems for video Technol., vol. 7, no. 5, pp. 924-929, Dec.
replacement algorithm is applied to further improve the                                                 1997.
performance. The performance of the algorithm improves as                                        [10] H. Peak, R.C. Kim, and S.U. Lee, "A DCT-based spatially adaptive post-
compression ratio increases. The reduction of discontinuity                                           processing technique to reduce the blocking artifacts in transform coded
                                                                                                      images", IEEE Trans. Circuit System Video Technol., vol. 10, no. 1, pp.
signifies that (see Table I and II) blocking artifacts are reduced                                    36-41, Feb. 2000.
and it can also be observed visually in Fig. 1, 2 and 3. It can                                  [11] T. Chen, H. R. Wu, and B. Qiu, "Adaptive postfiltering of transform
also be seen from Table I and Table II that the improvement in                                        coefficients for the reduction of blocking artifacts," IEEE Trans. Circuits
                                                                                                      Syst. Video Technol., vol. 11, pp. 594-602, May 2001.
PSNR for block boundary pixels is more as compared to over                                       [12] S.-F. Chang and D. G. Messerschmitt, "Manipulation and compositing of
all PSNR.                                                                                             MC-DCT compressed video," IEEE J. Select. Areas Commun., vol. 13,
  Thus, proposed approach for discontinuity reduction reduces                                         no. 1, pp. 1-11, Jan. 1995.
                                                                                                 [13] Shizhong Liu, and Alan C. Bovik, "Efficient DCT-Domain Blind
the blocking artifacts eficintl. Ths cmpuatinaly efficient
       the locin rtiact efficiently. This computationally eficent                                       Measurement and Reduction of Blocking Artifacts", IEEE trans. on
algorithm also gives very good result in terms of PSNR,                                                 circuits and systems for video technol., vol. 12, no. 12, pp. 1139-1149,
discontinuity measure (BPSNR) and the visual quality. It is                                             December 2002.
clear from the results that this algorithm gives very good                                       [14] Y. Luo, R.K. Ward, "Removing Trans. Image Process., of block-based
                                                                                                      DCT compressed images", IEEE
                                                                                                                                   the blocking artifacts
                                                                                                                                                          vol. 12, no. 7,
performance with minimum computational complexity.                                                    pp. 838-842 July 2003.
                                      IV CONCL
                                 I* COCUSIN SIONS                                               ~~~~~[15]Y. Zhao,reduction inand S. domain", Electronics Letters, vol.for blocking
                                                                                                         artifacts
                                                                                                                   G. Cheng
                                                                                                                              DCT
                                                                                                                                    Yu, "Post-processing technique
                                                                                                                                                                        40, no. 19,
  In this paper, a simple yet effective algorithm for reducing                                          p.29-3,1tSeemr204
blocking artifacts from DCT coded image is proposed.


                                                                                          2820

 Authorized licensed use limited to: Aricent Technologies (Holdings) Ltd. Downloaded on February 9, 2010 at 02:49 from IEEE Xplore. Restrictions apply.

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:48
posted:6/9/2011
language:English
pages:6