1. UNIT IV

2. Compression Principles
The principles behind compression are
Source encoders and destination decoders
Lossy and lossless compression
Entropy encoding
Source encoding
Text Compression is used to reduce the volume of information to be transmitted and to reduce the bandwidth that is required for its transmission.

3. Compression Principles
Source encoders and destination decoders:
The source encoder is the application of compression algorithm and destination decoder is the application of decompression algorithm.
Lossy compression algorithm
The characteristics of lossy compression algorithm are
Produces a version of source information
Have higher level of compression
Lossy compression is an irreversible one
Some information is lost after decompression
Depends on the sensitivity of eye and ear.

4. Compression Principles
Lossless compression algorithm.
The characteristics of lossless compression algorithm are
Reduce the amount of source information to be transmitted in such a way that, when compressed information is decompressed, there is no loss of information.
It is irreversible.
Compression ratio is less.
Compression is independent of the human response.

5. Compression Principles
Entropy encoding
Entropy encoding is lossless and independent of type of information that is being compressed. It is concerned solely with how the information is represented
Source Encoding:
It explots a particular property of the source information in order to produce an alternative form of representation that is either a compressed version of the original form or is mere amenable to the application of compression.
Differential Encoding
Deferential encoding is used in applications where the amplitude of the signal varies over a wide range and the difference between adjacent samples is small. Here the difference between adjacent samples is encoded and transmitted which leads to a lesser number of bits and therefore requiring less bandwidth.
Transform encoding
Transform encoding involves transforming the source information from one form to another, which leads to compression. In general, there is no loss of information associated with transformation operation and this technique is normally used for applications involving image and video.

6. Text compression Static coding
In static coding, the code words assigned to the alphabets do not change during the compression.
Dynamic coding
In dynamic coding, the code words are dynamically completed during compression. The code words for a particular alphabet are not fixed throughout the compression. Dynamic coding is also called adaptive coding

7. Text compression Static Huffman coding
With static Huffman coding the character string to be transmitted is first analyzed and then character types and their relative frequency are determined. The coding operation involved creating an unbalanced tree with some branches shorter then others.
In static Huffman coding, the degree of imbalance is a function of the relative frequency of occurrence of characters, the larger the spread, the more unbalanced is the tree. The resulting tree is known as Huffman code tree.

8. Text compression Arithmetic Coding
Using Huffman coding, the optimum entropy value will be obtained only if the probabilities are integer powers of half. Arithmetic coding always results in code words that satisfy Shannon’s formula. But arithmetic coding is complicated compared to Huffman coding.

9. Image Compression GIF:
GIF stands for graphics interchange format. It is used extensively with the Internet for representation and compression of graphical image. GIF reduces the number of possible colors that are present by choosing the 256 colors from the original set of 2^24 colors.
TIFF:
Tagged Image File Format is a bitmap graphics format that is ideal for high resolution printing to PostScript printers and imagesetters. Originally created as a scanning format, TIFF offers great flexibility for use in page layout applications in part due to multiple color modes, multiple compression types, and cross-platform compatibility.

10. Image Compression Digitized Documents: Termination Codes Table
Over scanning
Modified Huffman Codes.
Modes – Pass Mode, Vertical Mode and Horizontal Mode
Digitized Pictures
JPEG

11. JPEG and its Standards Image Block Preparation Forward DCT
Quantization
Run-length Encoding
Huffman encoding
Frame building
JPEG decoding