Image Data Compression
Image compression, the art and science of reducing the
amount of data required to represent an image, is one of the most useful and
commercially successful technologies in the field of digital image processing.
To better understand the need of compact image representation, consider the
amount of data required to represent a two-hour
standard definition television movie using 720 x 480 x 24-bit pixel arrays.
A digital movie is sequence of video frames in which each frame is a full-color still image. Image
compression concerned with minimizing the number of bits required to represent
an image. The simplest and most dramatic form of data compression is:
·
Sampling
·
Bandlimited images
Where an infinite number of pixel per unit area is reduced
to one sample without any loss of information.
Application of data compression are primarily in
transmission and storage of information. Image transmission applications are in
broadcast tv, business and education.
Typical television have images have spatial resolution of
approximately 512 x 512 pixels per frame. At 8 bit per pixel per color channel
and 30 frames per second.
Applications
of data compression are: -
1) Image transmission
applications are in broadcast television, remote sensing via satellite,
military communication via aircraft, radar and sonar, teleconferencing, computer
communications.
2) Image storage is
required for educational and business documents, medical images that arises in
computer tomography (CT), magnetic resonance imaging (MRI) and digital
radiology, motion picture, weather maps, and so on.
Image data compression falls into two categories. In first category, called predictive coading, are that exploit redundancy in the data. Redundancy is characteristic related to such factor as predictability, randomness, and smoothness in the data. Techniques such as delta modulation and differential pulse code modulation fall into this category.
Image data compression falls into two categories. In first category, called predictive coading, are that exploit redundancy in the data. Redundancy is characteristic related to such factor as predictability, randomness, and smoothness in the data. Techniques such as delta modulation and differential pulse code modulation fall into this category.
In the second category, called transform coding,
compression is achieved by transforming the given image into another array such
that large amount of information is packed into small number of samples.
According to Shannon’s
noiseless coding theorem it is possible to code, without distortion. The
maximum achievable compression C, defined by
C
= average rate bit of the original raw data (B)/ average bit of the encoded
data (H + ἑ)
Pixel
Coding: -In this technique each pixel is processed
independently, ignoring the inter pixel dependencies. In PCM (pulse code
modulation) the incoming video signal is sampled, quantized and coded by a
suitable code word.
In PCM the incoming video signal is sampled, quantized, and
coded by a suitable code word. The quantized output is generally coed by a
fixed-length binary code word having B bits. Commonly, 8 bits are sufficient
for monochrome broadcast or video conferencing quality images, whereas medical
images or color video signals may require 10 to 12 bits per pixel.
The number of bits needed for visual display of images can
be reduced to 4 to 8 bits per pixel by using companding, contrast quantization
or dithering techniques.
The
Huffman Coding Algorithm: -
1) Arrange
the symbol probabilities p(i) in decreasing order and consider them as leaf
nodes of a tree.
1) While
there is more than one node:
·
Merge the two nodes with simplest probability
to form a new node whose probability is the sum of two merged nodes.
·
Arbitrarily assign 1 and 0 to each pair of
branches merging into a node.
2) Read
sequentially from the root node to the leaf node where the symbol is located.
Coding and decoding is done simply by looking up values in
a table.
Image
compression standards, formats and containers
1 .
Still
images: -
— Binary
·
CCITT Group 3
·
CCITT Group 4
·
JBIG1
·
JBIG2
·
TIFF
— Continuous
Tone
·
JPEG
·
JPEG-LS
·
JPEG-2000 (joint photographic expert group)
·
BMP
·
GIF
·
PNG (portable network graphics)
·
TIFF (tagged image file format)
Video:
-
·
DV
·
H.261
·
H.262
·
H.263
·
H.264
·
MPEG-1
·
MPEG-2
·
MPEG-4
·
AVS (audio video standard)
·
HDV (high definition video)
·
QUICK TIME
·
VC-1
simple and easy :)
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