Efficient Image Compression Using Improved Huffman Coding With Enhanced Lempel ZIV CODING Approach

M.A.P. Manimekalai and Thusnavis Bella Mary

Efficient storage, retrieval and transmission pose a challenge in digital imaging, since it calls for an enormous number of bits to form an image. To achieve a high image quality, most of the systems utilize the huffman coding for lossless image compression. However, the conventional huffman coding method generally requires an initial statistical analysis of the file itself, and also it necessitates transmitting a large decoding table along with the file. To solve this problem, improved huffman coding with enhanced Lempel–Ziv–Welch (LZW) algorithm is introduced. In this research, MRI images are preprocessed by an adaptive median filter and separated into Region Of Interest (ROI) and Non Region Of Interest (non-ROI) with the help of region-based active contour model using level set approach. Clipped Histogram Equalization (CHE) with Artificial Bee Colony Algorithm (ABC) approach is used for improving the contrast enhancement. The ROI and Non-ROI parts are compressed using improved huffman coding with enhanced LZW algorithm and improved Embedded Zerotree Wavelet (EZW) algorithm respectively. Finally the image is decompressed at the receiving end. The results of experiment show that the proposed method attains high performance as compared to the existing method in terms of compression ratio, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).

Volume 12 | 01-Special Issue

Pages: 359-368

DOI: 10.5373/JARDCS/V12SP1/20201082