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JPEG image compression using MATLAB

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  1. Introduction
  2. Overview
  4. JPEG
  5. Redundancy
  6. Techniques
  7. Transform coding
  8. Techniques applied to JPEG compression
  9. Decompression procedure
  10. Huffman coding
  11. Coding
  12. Conclusion
  13. References

The paper deals with studying techniques for reducing the storage required saving an image, or the bandwidth required transmitting it. Image compression addresses the problem of reducing the amount of data required to represent a digital image. The underlying basis of the reduction process is the removal of redundant data. From a mathematical viewpoint, this amounts to transforming a 2-D pixel array into a statistically uncorrelated data set. The transformation is applied prior to storage or transmission of the image. In this paper implementation of basic JPEG compression using only basic Matlab functions is pursued. This included going from a basic grayscale bitmap image all the way to a fully encoded file which is decoded to grayscale bitmap using decompression algorithm.

[...] y = blkproc(x, ' * x * P2't, P y = blkproc(y, ' round(x , y = im2col(y, ' distinct' % break 8*8 blocks into columns xb = size(y, % get number of blocks y = y(order, % reorder column elements eob = + % create end-of-block symbol r = zeros(numel(y) + size(y, count = for j = 1:xb % process 1 block (col) at a time i = max(find(y(:, % find last non-zero element if isempty(i) % no nonzero block values end p = count + q = p + = eob]; count =count + i + % truncate trailing add eob' end % and add to output vector r((count + % delete unused portion of r y.size = uint16([xm y.numblocks = uint16(xb); y.quality = uint16(quality * 100); y.col = y.eob = eob; B. THE FUNCTION TO COMPRESSED IMAGE. DECOMPRESS THE JPEG Fig.5 decompressed 8*8 subimage. Any differences between the original and reconstructed subimage are a result of lossy nature of JPEG compression and decompression process. XI. [...]

[...] Every day an enormous amount of information is stored, processed and transmitted digitally. Companies provide business associates, investors and potential customers with financial data, annual reports, and inventory and product information over the internet. So the methods of compressing the data prior to storage and/or transmission are of significant practical and commercial interest. This work presents the compression of digital image using MATLAB by creating user defined functions. II. OVERVIEW The image compression systems are composed of two distinct structural blocks: an encoder and a decoder. [...]

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