Refers to reducing the amount of data required to represent a digital image.

Principle of compression:

reduce the redundant information, e.g.,

coding redundancy

• Coding redundancy is present when less than optimal code

words are used.

interpixel redundancy

• Interpixel redundancy results from correlations between the pixels of an image.

psychovisual redundancy

Psychovisual redundancy is due to data that is ignored by the human visual system

(i.e. visually non essential information).

Image compression

Why…….?

Principal objective: To minimize the number of bits required to represent an image.

*Intended to yield a compact representation of an image.

*Reducing the image storage.

*Transmission requirements.

Types of image compression

Image data compression methods fall into two common categories:

*Lossy compression

*Lossless compression

Lossy Compression

*A lossy compression method is one where compressing data and then decompressing it retrieves data that may well be different from the original, but is close enough to be useful in some way.

*Used to compress multimedia data (audio, video, still images), especially in applications such as streaming media and internet telephony. Provide higher levels of data reduction Result in a less than perfect reproduction of the

original image

Lossless Compression

*Also called Information preserving compression.

*Compress and decompress images without losing information.

Lossless techniques

*Run length encoding

* Huffman encoding

* LZW coding

* Area coding

RLE (Run length Encoding)

The RL code for a gray scale image is :{ Vi ,Ri} Vi is the intensity of pixel and Ri refers to the number of consecutive pixels with the intensity Vi .

Lossy techniques

*Transformation coding

* Vector quantization

* Fractal coding

* Block Truncation Coding

* Subband coding

Examples

Transformation coding

*In this coding scheme, transforms such as DFT and DCT are used to change the pixels in the original image into frequency domain coefficients (called transform coefficients).

*These coefficients have the energy compaction property i.e. energy of the original data being concentrated in only a few of the significant transform coefficients. Only those few significant coefficients are selected and the remaining are discarded.

JPEG

*Joint Photographic Experts Group created the standard.

*Lossy Compression Technique based on use of Discrete Cosine Transform (DCT)

Steps in JPEG Compression

*Divide Each plane into 8x8 size blocks.

*Compute DCT of each block

*Treat separately DC components of each block.

*Apply Quantization to discard values

*Separately encode DC components and transmit data.

JPEG Compression

JPEG Compression

Results…

Applications

*Broadcast TV via satellite.

* military communications via aircraft, teleconferencing.

* computer communications etc.

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