The term image refers to a 2-D light intensity function f (x, y), where
(x, y) denote spatial coordinates and the values of intensity function,’f’
at a point (x,y) are proportional to the brightness (gray level) of the
image at that point.
It is represented in matrix form where row and column indices identify
a point in image and the corresponding matrix element identifies the
brightness of the image at that point. These elements of the matrix are
called as PIXELS or Picture Elements or Image Elements.
The term digital image processing generally refers to the processing of
2-D data in an array of real or complex numbers represented by a finite
number of bits (binary digits).
To process an image so that the result is more suitable than the original
image for a specific application. There are several techniques used for
enhancement of images. Some of the common image enhancement
techniques are :-
Techniques used for Enhancement
POINT OPERATIONS: -
Clipping and Thresholding.
Image Subtraction and Change Detection:-
High Boost Spatial Filtering
Any image electronic means is likely to be degraded by the sensing
environment. The degradations many be in the form of sensor noise,
blur due to camera misfocus, relative object camera motion, random
atmospheric turbulence and so on.
The term “data compression” refers to the process of reducing the
amount of data required to represent a given quantity of information.
In digital image compression, three basic data redundancies can be
identified. They are:
1. Coding redundancy.
2. Inter pixel redundancy.
3. Psycho visual redundancy.
1. Objective Fidelity Criteria
2. Subjective Fidelity Criteria
Image Compression Models
A compression system consists of two distinct structural blocks, which
are shown below:
1) Encoder. 2) Decoder.
F(x,y) source channel channel source
Encoder encoder channel decoder decoder -f’(x,y)
Data Compression strategies:
1. Lossless Compression
2. Variable –length coding
Original data stream:
17 8 54 0 0 0 97 5 16 0 45 23 0 0 0 0 0 3 67 0 0 8 ..
Run length Encoded data:
17 8 54 03 97 5 16 0 1 45 23 05 3 67 02 8 ..
3. Huffman coding
4 Loosy compression
The methods for segmentation are generally based on one of the two
basic properties of the gray – level values.
1. Develops machine that could perform visual functions of living beings.
2. Space image applications
3. In archeology, physics and related fields high energy plasmas and electron
4. Radar and sonar images.
They motivate, captivate, educate and inform more than words