Implementation of Various JPEG Algorithm for Image Compression

Abstract

In this work we have implemented the Baseline JPEG standard using MATLAB. We have done both the encoding and decoding of grayscale images in JPEG. With this project we have also shown the differences between the compression ratios and time spent in encoding the images with two different approaches viz-a-viz classic DCT and fast DCT. The project also shows the effect of coefficients on the image restored. The steps in encoding starts with first dividing the original image in 8X8 blocks of sub- images. Then DCT is performed on these sub-images separately. And it is followed by dividing the resulted matrices by a Quantization Matrix. And the last step in algorithm is to make the data one-dimensional which is done by zigzag coding and compressed by Huffman coding, run level coding, or arithmetic coding. The decoding process takes the reverse process of encoding. Firstly, the bit-stream received is converted back into two-dimensional matrices and multiplied back by Quantization Matrix. Then, the Inverse DCT is performed and the sub-images are joined together to restore the image. In this paper we have discuss JPEG compression using MATLAB in particular we are using DCT, Zig zag, compressed by Huffman coding, run level coding or arithmetic coding.