Authors : C. Senthilkumar and R.K. Gnanamurthy
Abstract: Image compression is the art and science of removing redundancies to represent information in a compact form. In this study, we have reviewed the performance of wavelet based compression techniques such as Embedded Zero Tree (EZW) and Set Partitioning In Hierarchical Tree (SPIHT). These methods combine stepwise thresholding and progressive quantization, focusing on more efficient way to encode the image coefficients in order to obtain better compression ratio. The redundancies are removed while the compression of image is coding, inter-pixel, psycho-visual and chromatic redundancies. The problems associated with image compression are aliasing, noise and artifacts. Lossless Compression algorithms preserve information and the compression process incurs no data loss but lossy compressions incur a loss of information. The applications of image compression are videoconferencing, satellite imaging, medical imaging, image transmission in internet, etc. The image parameters including file size, MSE, BPP and PSNR values of different wavelets are analyzed and results were discussed.
C. Senthilkumar and R.K. Gnanamurthy, 2014. A Performance Analysis of EZW, SPIHT Wavelet Based Compressed Images. Asian Journal of Information Technology, 13: 684-688.