Image Compression using Lifting Wavelet Transform

Wavelet transform, due to its time frequency characteristics, has been a popular multiresolution analysis tool. Its discrete version, i.e. DWT has been widely used in various applications till date. The hugely applied version of DWT is convolution based. But for hardware implementation this convolution based system has had problems with floating point numbers. Thus the lifting based DWT method, with less cost of computation, more efficient performance and easier hardware implementability has become popular. Here image compression scheme using this lifting based DWT method is presented. The quality analysis of this method has been checked for three different levels of DWT scaling, with varying quantization levels with lossless encoding scheme. The image quality analysis has been done using two sets of parameters, namely the popular peak signal to ratio method and the block based median singular value decomposition method of Shnyderman, et. al. Based on these two image quality assessments, this method along with its properties of easier hardware computation may be easily realized for real time image compression for real time devices and systems at lower costs. Keywords—DWT, lifting, peak signal to noise ratio, block based median singular value decomposition