Still Image Compression by Combining EZW Encoding with Huffman Encoder

Abstract

Image compression can improve the performance of the digital systems by reducing time and cost in image storage and transmission without significant reduction of the image quality. For image compression it is desirable that the selection of transform should reduce the size of resultant data set as compared to source data set. EZW is computationally very fast and among the best image compression algorithm known today. This paper proposes a technique for image compression which uses the Wavelet-based Image Coding in combination with Huffman encoder for further compression. A large number of experimental results are shown that this method saves a lot of bits in transmission, further enhances the compression performance. This paper aims to determine the best threshold to compress the still image at a particular decomposition level by combining the EZW encoder with Huffman Encoder. Compression Ratio (CR) and Peak-Signalto-Noise (PSNR) is determined for different threshold values ranging from 6 to 60 for decomposition level 8.