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A primer on image compression

20 Feb 2015  | Sunny Aggarwal, Gourav Modi

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DCT on 8x8 block
Steps to be performed:

 • Take a 8x8 matrix of an image and fetch its value from 0 to 256
 • Scale it down to -128 to 127 level
 • Ready to perform the DCT matrix ( D= TMT' )
 • Quantisation
An 8x8 block of DCT is compressed using quantisation. A remarkable feature of JPEG Process is : the varying levels of image compression and quality is obtainable by using different quantisation matrix.

Example of a Quantisation matrix:


After calculating the DCT equivalent of an image, the matrix is divided by the quantisation matrix to the nearest integer (lossy) and thereby making the higher frequency content to be nearly zero.


Coding
The matrix is ready for the final step of compression. Before storage, the coefficients are converted to a stream of binary data. After quantisation, the higher frequency components become zero, JPEG takes advantage of this by encoding quantised coefficients in the zigzag sequence

Figure 6: Zigzag sequence for coding.


Encoding
RLE algorithm is applied to condense sequences of identical values. Finally, Huffman compression is done to the remaining sequence which encodes frequently used values using lesser bits than infrequently used values.

Figure 7: Encoding using RLE.


About the authors
Sunny Aggarwal and Gourav Modi contributed this article.


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