Image compression based upon Wavelet Transform and a statistical threshold

摘要

Discrete Wavelet Transform, (DWT), is known to be one of the best compression techniques. It provides a mathematical way of encoding information in such a way that it is layered according to level of detail. In this paper, we used Haar wavelets as the basis of transformation functions. Haar wavelet transformation is composed of a sequence of low pass and high pass filters, known as filter bank. The redundancy of the DWT detail coefficients are reduced through thresholding and further through Huffman encoding. The proposed threshold algorithm is based upon the statistics of the DWT coefficients. The quality of the compressed images has been evaluated using some factors like Compression Ratio, (CR), and Peak Signal to Noise Ratio, (PSNR). Experimental results demonstrate that the proposed technique provides sufficient higher compression ratio compared to other compression thresholding techniques.