Docstoc

UBICC-233 233

Document Sample
UBICC-233 233 Powered By Docstoc
					     A HYBRID TRANSFORMATION TECHNIQUE FOR ADVANCED
                      VIDEO CODING

                                    M. Ezhilarasan, P. Thambidurai
                 Department of Computer Science & Engineering and Information Technology,
                       Pondicherry Engineering College, Pondicherry – 605 014, India
                                           mrezhil@yahoo.com


                                                 ABSTRACT
               A Video encoder performs video data compression by having combination of three
               main modules such as Motion estimation and compensation, Transformation, and
               Entropy encoding. Among these three modules, transformation is the module of
               removing the spatial redundancy that exists in the spatial domain of video
               sequence. Discrete Cosine Transformation (DCT) is the defacto transformation
               method in existing image and video coding standards. Even though the DCT has
               very good energy preserving and decorrelation properties, it suffers from blocking
               artifacts. To overcome this problem, a hybridization method has been incorporated
               in transformation module of video encoder. This paper presents an hybridization in
               the transformation module by incorporating DCT as transformation technique for
               inter frames and a combination of wavelet filters for intra frames of video
               sequence. This proposal is also applied in the existing H.264/AVC standard.
               Extensive experiments have been conducted with various standard CIF and QCIF
               video sequences. The results show that the proposed hybrid transformation
               technique outperforms the existing technique used in the H.264/AVC considerably.

               Keywords: Data Compression, DCT, DWT, Video Coding, Transformation.


1   INTRODUCTION                                               In Advanced Video Coding (AVC) [6], video is
                                                          captured as a sequence of frames. Each frame is
     Transform coding techniques have become the          compressed by partitioning it as one or more slices,
important paradigm in image and video coding              where each slice consists of sequence of macro
standards, in which the Discrete Cosine Transform         blocks. These macro blocks are transformed,
(DCT) [1][2] is applied due to its high decorrelation     quantized and encoded. The transformation module
and energy compaction properties. In the past two         converts the frame data from time domain to
decades, more contributions focused on Discrete           frequency domain, which intends to decorrelate the
Wavelet Transform (DWT) [3][4] for its                    energy (i.e., amount of information present in the
performance in image coding. The two most popular         frame) present in the spatial domain. It also converts
techniques such as DCT and DWT are well applied           the energy components of the frame into small
on image and video coding applications.                   numbers of transform coefficients, which are more
International Organization for Standards /                efficient for encoding rather than their original
International     Electro   technical    Commission       frame. Since the transformation module is reversible
(ISO/IEC) and International Telecommunications            in nature, this process does not change the
Union – Telecommunication standardization sector          information content present in the source input signal
(ITU-T) organizations have developed their own            during encoding and decoding process. By
video coding standards viz., Moving Picture Experts       information theory, transformed coefficients are
Group MPEG-1, MPEG-2, MPEG-4 for multimedia               reversible in nature.
and H.261, H.263, H.263+, H.263++, H.26L for                   As per Human Visual System (HVS), human
videoconferencing applications. Recently, the MPEG        eyes are highly sensitive on low frequency signals
and the Video Coding Experts Group (VCEG) have            than the high frequency signals. The decisive
jointly designed a new standard namely, H.264 /           objective is this paper is to develop a hybrid
MPEG-4 (Part-10) [5] for providing better                 technique that achieves higher performance in the
compression of video sequence. There has been a           parameters specified above than the existing
tremendous contribution by researchers, experts of        technique used in the current advanced video coding
various institutions and research laboratories for the    standard.
past two decades to take up the recent technology              In this paper, a combination of orthogonal and
requirements in the video coding standards.               bi-orthogonal wavelet filters have been applied at


                     Ubiquitous Computing and Communication Journal                                           1
different decomposition levels for intra frames and    2.1        Basics of Transformation
DCT for inter frames of video encoder. Even though
intra frames are coded with wavelet transform, the          From the basic concepts of information theory,
impact of this can be seen in inter frame coding.      coding of symbols in vectors is more efficient than
With better quality anchor pictures are retained in    coding of symbols in scalars [8]. By using this
frame memory for prediction, the remaining inter       phenomenon, a group of blocks of consecutive
frame pictures are more efficiently coded with DCT.    symbols from the source video input are taken as
The proposed transformation method is also             vectors. There is high correlation in the neighboring
implemented on H.264/AVC reference software [7].       pixels in an image or intra-frame of video.
The paper is organized as follows. In Section 2, the   Transformation is a reversible model [9] by theory,
basics of the transform coding methods are             which decorrelates the symbols in the given blocks.
highlighted. The proposed hybrid transformation        In the recent image and video coding standards the
technique has been described in section 3. Extensive   following transformation techniques are applied due
experimental results and discussion have been given    to their orthonormal property and energy
in section 4 followed by conclusion in section 5.      compactness.

2   BASICS OF TRANSFORM CODING                         2.1.1 Discrete Cosine Transform
                                                            The Discrete Cosine Transform, a widely used
    For any inter-frame video coding standards, the    transform coding technique in image and video
basic functional modules are motion estimation and     compression algorithms. It is able to perform de-
compensation, transformation, quantization and         correlation of the input signal in a data-independent
entropy encoder. As shown in the Fig. 1, the           manner. When an image or a frame is transformed by
temporal redundancies exists in successive frames      DCT, it is first divided into blocks, typically of size
are minimized or reduced by motion estimation and      of 8x8 pixels.        These pixels are transformed
compensation module. The residue or the difference     separately without any influence from the other
between the original and motion compensated frame      surrounding blocks. The top left coefficient in each
is applied into the sequence of transformation and     block is called the DC coefficient, and is the average
quantization modules. The spatial redundancy exists    value of the block. The right most coefficients in the
in neighboring pixels in the image or intra-frame is   block are the ones with highest horizontal frequency,
minimized by these modules.                            while the coefficients at the bottom have the highest
                                                       vertical frequency. This implies that the coefficient
                                                       in the bottom right corner has the highest frequencies
                                                       of all the coefficients.
                                                            The forward DCT of a discrete signal for
                                                       original image f(i,j) for (MxN) block size and inverse
                                                                                                %
                                                       DCT (IDCT) of reconstructed image f (i, j) for the
                                                       same (MxN) block size are defined as

                                                                   2C(u)C(v) M −1 N −1 (2i + 1)uπ (2 j + 1)vπ                    (1)
                                                       F(u,v) =              ∑ ∑ cos 2M cos 2 N f (i , j )
                                                                      MN i =0 j = 0


                                                               M −1 N −1
                                                                           2C(u)C(v)     (2i + 1)uπ     (2 j + 1)vπ              (2)
                                                       f(i,j) = ∑ ∑
                                                       %                             cos            cos             F (u , v )
                                                                u = 0 v =0    MN            2M              2N


                                                       Where i, u = 0,1,…,M-1, j, v = 0,…,N-1 and the
Figure 1: Basic Video encoding module.
                                                       constants C(u) and C(v) are obtained by
                                                                               2
    The transformation module converts the residue                 C ( x) =           if x = 0
                                                                              2
symbols from time domain into frequency domain,
which intends decorrelate the energy present in the                        =1          otherwise
spatial domain. This is so appropriate for
quantization. Quantized transform coefficients and         MPEG standards apply DCT for video
motion displacement vectors obtained from motion       compression. The compression exploits spatial and
estimation and compensation module are applied into    temporal redundancies which occur in video objects
entropy encoding (Variable Length Coding) module,      or frames. Spatial redundancy can be utilized by
where it removes the statistical redundancy. These     simply coding each frame separately. This technique
modules are briefly introduced as follows.             is referred to as intra frame coding. Additional
                                                       compression can be achieved by taking advantage of
                                                       the fact that consecutive frames are often almost
                                                       identical. This temporal compression has the




                    Ubiquitous Computing and Communication Journal                                                                     2
potential for a major reduction over simply encoding             φ (t ) = ∑ 2h0 [n]φ (2t − n)              (3)
each frame separately, but the effect is lessened by                       n∈Z
the fact that video contains frequent scene changes.       The dilation function is recipes for finding a function
This technique is referred to as inter-frame coding.       that can be build from a sum of copies of itself that
The DCT and motion compensated Inter-frame                 are scaled, translated, and dilated. Equation (3)
prediction are combined. The coder subtracts the           expresses a condition that a function must satisfy to
motion-compensated prediction from the source              be a scaling function and at the same time forms a
picture to form a ‘prediction error’ picture. The          definition of the scaling vector h0. The wavelet at the
prediction error is transformed with the DCT, the          coarser level is also expressed as
coefficients are quantized using scalar quantization            ψ (t ) = ∑ 2h1 [ n]φ (2t − n)              (4)
and these quantized values are coded using an                                  n∈Z
arithmetic coding. The coded luminance and                 The discrete high-pass impulse response h1[n],
chrominance prediction error is combined with ‘side        describing the details using the wavelet function, can
information’ required by the decoder, such as motion       be derived from the discrete low-pass impulse
vectors and synchronizing information, and formed          response h0[n] using the following equation.
into a bit stream for transmission. This technique             h1 [n] = (−1) n h0 [1 − n]                   (5)
works well with a stationary background and a
                                                           The number of coefficients in the impulse
moving foreground since only the movement in the
                                                           coefficients in the impulse response is called the
foreground is coded.
     Despite all the advantages of JPEG and MPEG           number of taps in the filter. For orthogonal filters,
compression schemes based on DCT namely                    the forward transform and its inverse are transposing
simplicity, satisfactory performance, and availability     of each other, and the analysis filters are identical to
                                                           the synthesis filters.
of special purpose hardware for implementation;
these are not without their shortcomings. Since the
input image needs to be “blocked,” correlation across      2.2     Quantization
                                                                A Quantizer [10][11] simply reduces the number
the block boundaries is not eliminated. The result is
noticeable and annoying “blocking artifacts”               of bits needed to store the transformed coefficients
particularly at low bit rates.                             by reducing the precision of those values. Since this
                                                           is a many to one mapping, it is a lossy process and is
                                                           the main source of compression in an encoder.
2.1.2 Discrete Wavelet Transform
                                                           Quantization can be performed on each individual
     Wavelets are functions defined over a finite
interval and having an average value of zero. The          coefficient, which is referred as scalar quantization.
basic idea of the wavelet transform is to represent        Quantization can also be performed on a group of
any arbitrary function as a superposition of a set of      coefficients together, and which is referred as vector
                                                           quantization.
such wavelets or basis functions. These basis
functions or child wavelets are obtained from a                 Uniform quantization is a process of partitioning
single prototype wavelet called the mother wavelet,        the domain of input values into equally spaced
by dilations or scaling and translations. Wavelets are     intervals, except outer intervals. The end points of
used to characterize detail information.            The    partition intervals are called the quantizer decision
averaging information is formally determined by a          boundaries. The output or reconstruction value
kind of dual to the mother wavelet, called the scaling     corresponding to each interval is taken to be the
                                                           midpoint of the interval. The length of each interval
function φ (t). The main concept of wavelets is that       is referred to as the step size (fixed in the case of
at a particular level of resolution j, the set of          uniform quantization), denoted by the symbol ∆.
translates indexed by n form a basis at that level.        The step size ∆ is given by
The set of translates forming the basis at the j+1 next               2X max
                                                                 ∆=                                         (6)
level, a coarser level, can all be written as a sum of                 M
weights times the level-j basis. The scaling function      Where M = number of level of quantizer, Xmax is the
is chosen such that the coefficients of its translation    maximum range of input symbols.
are all necessarily bounded.                                   In this work, a quantizer used in H.264 has been
     The scaling function, along with its translation,     considered for inter-frame motion compensated
forms a basis at the coarser level j+1 but not level j.    predictive coding, which allows acceptable loss in
Instead, at level j the set of translates of the scaling   quality for the given video sequences.
function φ (t) along with the set of translates of the
mother wavelet   φ (t) do form a basis. Since the set of   2.3    Motion Estimation
                                                               Motion estimation (ME) [12] is a process to
translates of the scaling function φ (t) at a coarser      estimate the pixels of the current frame from
level can be written exactly as a weighted sum of          reference frame(s). Block matching motion
translates at a finer level, the scaling function must     estimation or block matching algorithm (BMA),
satisfy the dilation function                              which is temporal redundancy removal technique



                     Ubiquitous Computing and Communication Journal                                               3
between two or more successive frames, is an                                           coding is more complex than Huffman coding on its
integral part for most of the motion compensated                                       implementation. CAVLC used in H.264 has been
video coding standards. Frames are being divided                                       considered in the experiments for entropy encoding
into regular sized blocks, so referred as macro blocks                                 process.
(MB). Block-matching method is to find the best-
matched block from the previous frame. Based on a                                      2.5    Motivation for this work
block distortion measure (BDM), the displacement of                                         DCT is best transformation technique for Motion
the best-matched block will be described as the                                        estimation and compensated predictive coding
motion vector (MV) to the block in the current frame.                                  models.      Due to blocking artifacts problems
The best match is usually evaluated by a cost                                          encountered in DCT, sub band coding methods are
function based on a BDM such as Mean absolute                                          considered as an alternative for this problem. DWT
difference (MAD) defined as                                                            is the best alternative method because of its energy
                     1 M −1 N −1 | c( x + k , y + l ) − p( x + k + i, y + l +          compaction and preservation property. Due to
                    MN ∑ ∑
      MAD(i, j) =                                                               j) |
                       k =0 l =0
                                               (7)                                     ringing artifacts incurred in DWT, there is a
where M x N is the size of the macro block, c(.,.) and                                 tremendous contribution from the researchers,
p(.,.) denote the pixel intensity in the current frame                                 experts from various institutes and research labs for
and previously processed frames respectively, (k,l) is                                 past two decades.
the coordinates of the upper left corner of the current                                     In addition to the transformation module, In
block, and (x,y) represents the displacement in pixel                                  DCT-based        Motion    compensated       Predictive
which is relative to the position of current block.                                    (MCP) [15] coding architecture, previously
After checking each location in the search area, the                                   processed frames are considered as reference frames
motion vector is then determined as the (x,y) at                                       to predict the future frames. Even though the
which the MAD has the minimum value. In this wok,                                      transformation module is energy preserving and
an exhaustive full search has been applied for motion                                  lossless module, it is irreversible in experiments.
compensated prediction technique.                                                      Subsequently the transformed coefficients are
                                                                                       quantized to achieve higher compression leads
2.4    Entropy Encoding                                                                further loss in the frame, which are to be considered
     Based on scientist Claude E. Shannon [8], the                                     as reference frames stored in frame memory for
entropy η of an information source with alphabet S =                                   future frame prediction. Decoded frames are used for
{s1, s2, …, s3} is defined as                                                          the prediction of new frames as per the MCP coding
                    n
                                     1                                                 technique. JPEG 2000 [16] proved that high quality
η = H ( S ) = ∑ pi log 2
                i =1                 pi                                                image compression can be achieved by applying
                                               (8)
                                                                                       DWT. This motivates us to have a combination of
Where pi is the probability of symbol si in S. The
                                                                                       orthogonal and bi-orthogonal wavelet filters at
term log2 1 indicates the amount of information                                        different level of decompositions for intra frames and
               pi

contained in si, which corresponds to the number of                                    DCT for inter frames of video sequence.
bits needed to encode si. An entropy encoder further
compresses the quantized values to give better                                         3     PROPOSED HYBRID TRANSFORMATION
compression ratio. It uses a model to accurately                                             WITH DIFFERENT COMBINATION OF
determine the probabilities for each quantized value                                         WAVELET FILTERS
and produces an appropriate code based on these
probabilities so that the resultant output code stream                                      In order to improve the efficiency of
will be smaller than the input stream. The most                                        transformation phase, the following techniques are
commonly used entropy encoders are the Huffman                                         adopted in the transformation module of the
encoder [13] and the arithmetic encoder [14]. It is                                    CODEC. Orthogonal wavelet filters such as Haar
important to note that a properly designed entropy                                     filter and Daubechies 9/7 filters are considered for
encoder is absolutely necessary along with optimal                                     intra frames and Discrete Cosine Transform for inter
signal transformation to get the best possible                                         frames of video sequence. Figure 2 illustrates an
compression.                                                                           overview of the encoder of H.264/AVC with a
     Arithmetic coding is a more modern coding                                         hybrid     transformation     technique.     Previously
method that usually outperforms Huffman coding in                                      processed frames (F’n-1) are used to perform Motion
practice. In arithmetic coding, a message is                                           Estimation and Motion Compensated Prediction,
represented by an interval of real numbers between 0                                   which yields motion vectors.
and 1. As the message becomes longer, the interval                                      These motion vectors are used to make a motion
needed to represent it becomes smaller, and the                                        compensated frame. In the case of inter frames, the
number of bits needed to specify that interval grows.                                  frame is subtracted from the current frame (Fn) and
Successive symbols of the message reduce the size of                                   the residual frame is transformed using Discrete
the interval in accordance with the symbol                                             Cosine Transform (T) and quantized (Q). In the case
probabilities generated by the model. The arithmetic                                   of intra frame, the current frame is transformed using




                                    Ubiquitous Computing and Communication Journal                                                          4
Discrete Wavelet Transform (DWT) with different                                             avoidance of undesirable blocking artifacts, the intra
orthogonal wavelet filters such as Haar and                                                 frame is reconstructed with high quality. The first
Daubechies and quantized (Q). The quantized                                                 frame in a GOF is intra frame coded. Frequent intra
transform coefficients are then entropy coded and                                           frames enable random access to the coded stream.
transmitted or stored through NAL along with the                                            Inter frames are predicted from previously decoded
motion vectors found in the motion estimation                                               intra frames.
process.
                                         +                          X
                                                                                            4    EXPERIMENTAL                      RESULTS          AND
Fn                                                    T       Q         Reorder   Entropy
                                                                                  encoder        DISCUSSION
                      ME

                                         Inter       DWT
F’n-1                      MC                                                      NAL         The experiments were conducted for three CIF
              Choose           Intra     Intra
                                                                                            video sequences such as “Bus” (352x288, 149
                intra
             prediction
                            prediction
                                                     IDWT
                                                                                            frames), “Stefan” (352x288, 89 frames) and “Flower
                                             +
                                                 +
                                                                                            Garden” (352x288, 299 frames), and two QCIF
F’n          Filter                                   IT      Q’1
                                                                                            video sequences like “Suzie” (176x144, 149 frames)
                                                                                            and “Mobile” (176x144, 299 frames).             The
Figure 2: Encoder in the hybrid transformation with
                                                                                            experimental results show that the developed hybrid
wavelet filters.
                                                                                            transform coding with wavelet filters combination
                                                                                            outperforms over conventional DCT based video
   For predicting the subsequent frames from the
                                                                                            coding in terms of quality performance.
anchor intra frames, the quantized transform
                                                                                                Peak Signal to Noise Ratio (PSNR) is commonly
coefficients are again dequantized (Q’1) followed by
                                                                                            used to measure the quality. It is obtained from
inversely transformed (IT) and retained in the frame
                                                                                            logarithmic scale and it is Mean Squared Error
store or store memory for motion compensated
                                                                                            (MSE) between the original and reconstructed image
prediction.
                                                                                            or video frame with respect to the highest available
                                                                                            symbol in the spatial domain.
Table 1: Biorthogonal wavelets filter coefficients.
                                                                                                                        (2 n − 1) 2                 (9)
                           Analysis Filter Coefficients                                         P S N R = 1 0 log 1 0               dB
                                                                                                                          M SE
        i             Lowpass Filter g L(i)                 Highpass Filter g H(i)
        0             0.602949018236359                     1.115087052456994               where n is the number of bits per image symbol.
        ±1            0.266864118442872                                 -
        ±2                          -                                   -                        The fundamental tradeoff is between bit rate and
                                                                                            fidelity [17]. The ability of any source encoding
        ±3                          -                       0.091271763114249               system is to make this tradeoff as acceptable by
        ±4            0.026748757410809                                 -                   keeping moderate coding efficiency.
                           Synthesis Filter Coefficients
        i             Lowpass Filter h L(i)                 Highpass Filter h H(i)          Table 2: Proposed combination of wavelets filters.
        0             1.115087052456994                     0.602949018236379                    Proposed             1st level            2nd level
        ±1            0.591271763114247                                 -                       combination        Decomposition         Decomposition
        ±2                          -                                   -                           P1                  Haar                 Haar
                                                                                                    P2                  Haar                 Daub
        ±3                          -                       0.016864118442874                       P3                 Daub                  Haar
        ±4                          -                       0.026748757410809                       P4                 Daub                  Daub

     In the case of intra frames, inverse Discrete                                              Table 2 shows the combination of orthogonal
Wavelet Transform is applied in order to obtain                                             Haar and Daubechies 9/7 wavelet filters in different
reconstructed reference frames (F’n) through de-                                            level of decompositions in transform coding. These
blocking filter for inter frames of video sequence.                                         combinations are simulated in H.264/AVC codec,
The hybrid transformation technique employs                                                 where the DCT is the de-facto transformation
different techniques for different categories of frames.                                    technique for both intra frame and inter frames of
Intra frames are coded using both Haar wavelet filter                                       video sequence processing.
coefficients [0.707, 0.707] and bi-orthogonal                                                   Table 3 shows the performance comparison of
Daubechies 9/7 wavelet filter coefficients as shown                                         the quality parameter in terms of Peak Signal-to-
in Table 1 [16] in different combinations on different                                      Noise Ratio (PSNR) for the existing de-facto DCT
decomposition levels. Because of wavelet’s                                                  transformation with combination of proposed
advantages over DCT such as complete spatial                                                wavelet filters. The values in the table represent the
correlation among pixels in the whole frame,                                                average PSNR improvement for Luminance (Y)




                                             Ubiquitous Computing and Communication Journal                                                               5
component and Chrominance (U and V) components.             considered in this paper includes the PSNR
As per Human Vision System, human eyes are                  performance. The performance evaluations show that
highly sensitive on Luminance than the Chrominance          the hybrid transformation technique outperforms the
components. In this analysis, both Luminance and            existing DCT transformation method used in
Chrominance components are considered due to the            H.264/AVC significantly. The experimental results
importance of colour in near lossless applications.         also demonstrate that the combination of Haar
There is 0.12 dB Y-PSNR improvement in P4                   wavelet filter in 1st level of decomposition and
combination with DCT transformation for ‘Bus’ CIF           Daubechies wavelet filters in 2nd level of
sequence. When the comparison has been made for             decomposition outperforms other combination and
‘Stefan’ CIF sequence, 0.31 dB Y-PSNR                       the original DCT used in the existing AVC standard.
improvement has been achieved in P1 combination
with existing transformation. 0.14 dB Y-PSNR                ACKNOWLEDGEMENT
quality has been obtained with DCT transformation               The authors wish to thank S. Anusha, A. R.
in P4 combination for ‘Flower-Garden’ CIF                   Srividhya, S. Vanitha, V. Rajalakshmi, R. Ramya, M.
sequence.                                                   Vishnupriya A. Arun, V. Vijay Anand, S. Dhinesh
                                                            Kumar and P. Navaneetha Krishnan undergraduate
Table 3: PSNR comparison for the various video              students for their valuable help.
sequences.
                                                            6     REFERENCES
                 Existing    P1       P2      P3      P4
Sequence PSNR
                  (dB)      (dB)     (dB)    (dB)    (dB)   [1]  Zixiang Xiong, Kannan Ramachandran,
             Y    35.77     35.03   35.88   35.88   35.89        Michael T. Orchard and Ya-Qin Zhang: A
     Bus     U    35.83     35.81   35.83   35.82   35.82        Comparative study of DCT and Wavelet-Based
             V    36.04     36.03   36.04   36.03   36.03
                                                                 Image Coding, IEEE Transactions on Circuits
             Y    36.38     35.69   36.50   36.50   36.50
    Stefan   U    35.00     35.00   35.01   35.00   35.00        and Systems for Video Technology, Vol. 9,
             V    36.90     36.90   36.91   36.91   36.91        No. 5, pp. 692-695 (1999).
             Y    36.00     35.72   36.13   36.13   36.14   [2] N. Ahmed, T. Natarajan and K. R. Rao:
    Flower
    Garden
             U    36.51     36.49   36.47   36.50   36.50        Discrete Cosine Transform, IEEE Transactions
             V    34.93     34.92   34.93   34.94   34.93        on Computers, pp. 90-93 (1974).
             Y    37.62     37.57   37.66   37.68   37.68   [3] Ingrid Daubechies: Ten lectures on wavelets,
     Suzie   U    43.76     43.71   43.72   43.75   43.74
                                                                 Capital city Press, Pennsylvania, pp. 53-105
             V    43.32     43.35   43.43   43.39   43.39
             Y    33.95     33.92   34.10   34.10   34.10        (1992).
    Mobile   U    35.13     35.12   35.10   35.08   35.08   [4] Marc Antonini, Michel Barlaud, Pierre Mathieu
             V    34.92     34.96   34.91   34.91   34.91        and Ingrid Daubechies: Image coding using
                                                                 wavelet transform, IEEE Transactions on
     As per QCIF sequences such as ‘Suzie’ and                   Image Processing, Vol. 1, No. 2, pp. 205-220
‘Mobile’ are concerned, up to 0.15 dB Y-PSNR                     (1992).
improvement has been achieved when the bi-                  [5] Gary J. Sullivan, Pankaj Topiwala and Ajay
orthogonal wavelet filters are considered in the 2nd             Luthra: The H.264/AVC AVC Standard -
level of decomposition of the wavelet operation for              Overview and Introduction to the Fidelity
intra frames of the video sequences. In both CIF and             Range Extensions, SPIE Conference on
QCIF video sequences, a comparable quality                       Applications of Digital Image Processing
improvement has been attained as per Luminance                   XXVII (2004).
components such as U-PSNR and V-PSNR are                    [6] Iain E. G. Richardson: H.264 and MPEG-4
concerned.                                                       Video Compression, John Wiley & Sons (2003).
                                                            [7] ftp://ftp.imtc.org/jvt-experts/reference_software.
5      CONCLUSION                                           [8] C. E. Shannon: A Mathematical theory of
                                                                 Communication, Bell System Technical Journal,
   In this paper, a hybrid transformation technique              Vol. 27, pp. 623-656 (1948).
for advanced video coding has been proposed. In             [9] Kelth Jack: Video Demystified, Penram
which, the intra frames of video sequence are coded              International Publishing Pvt. Ltd., Mumbai,
by DWT with Haar and Daubechies wavelet filters                  pp. 234-236 (2001).
and the inter frames of video sequence are coded            [10] Allen      Gersho:       Quantization,     IEEE
with DCT technique. The hybrid transformation                    Communications Society Magazine, pp. 16-29
technique is also simulated in the existing                      (1977).
H.264/AVC reference software. Experiments were              [11] Peng H. Ang, Peter A. Ruetz and David Auld:
conducted with various standard CIF and QCIF                     Video compression makes big gains, IEEE
video sequences such as Bus, Stefan, Flower-Garden,              Spectrum (1991).
Mobile and Suzie. The performance parameter                 [12] Frederic Dufaux, Fabrice Moscheni:Motion




                      Ubiquitous Computing and Communication Journal                                            6
     Estimation Technique for Digital TV-A Review          standards for Image, Video and Audio Coding,
     and a New Contribution, Proceedings of IEEE,          NJ, Prentice Hall, pp. 85-96 (1996).
     Vol. 83, No. 6, pp. 858-876 (1995).              [16] B. E. Usevitch: A Tutorial on Modern Lossy
[13] D. A. Huffman: A Method for the Construction          Wavelet Image Compression-Foundations of
     of Minimum-Redundancy Codes, Proceedings              JPEG 2000, IEEE Signal Processing Magazine,
     of IRE, Vol. 40, No. 9, pp. 1098-1101 (1952).         Vol. 18, No. 5, pp. 22-35 (2001).
[14] P. G. Howard, J. C. Vitter: Arithmetic Coding    [17] Gary J. Sullivan, Thomas Wiegand: Video
     for Data Compression, Proceedings of the IEEE,        Compression – from concepts to the
     Vol. 82, No. 6, pp. 857-865 (1994).                   H.264/AVC standard, Proceedings of IEEE,
[15] K. R. Rao, J. J. Hwang: Techniques and                Vol. 93, No. 1, pp. 18-31 (2005).




                   Ubiquitous Computing and Communication Journal                                    7

				
DOCUMENT INFO
Shared By:
Categories:
Tags: UbiCC, Journal
Stats:
views:15
posted:6/17/2010
language:English
pages:7
Description: UBICC, the Ubiquitous Computing and Communication Journal [ISSN 1992-8424], is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. With a world-wide membership, UBICC is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society.
UbiCC Journal UbiCC Journal Ubiquitous Computing and Communication Journal www.ubicc.org
About UBICC, the Ubiquitous Computing and Communication Journal [ISSN 1992-8424], is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. With a world-wide membership, UBICC is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society.