Wavelet compression techniques for digital image optimization

Abstract

A visual information given by a digital image consumes enormous storage capacity. Moreover, the memory, bandwidth and computational power required to store, transmit and processes a typical digital image is very expensive. Therefore, image compression is necessary to represent a digital image with the smallest possible number of bits without suffering any information loss as well as speeding up the transmission and minimizing storage requirement. This project employs Wavelet Transform to compress still image as this technique currently provide the most promising approach to highquality image compression. Comparison with JPEG compression were carried out on relevant aspect of the Human Visual System (HVS) and image quality assessment measurement such as the mean square error (MSE) and the peak signal-tonoise ratio (PSNR) by means of MATLAB® software. Finally, the findings proposed the Wavelet compressed image is more natural and pleasing to the eye. The results suggest that Wavelet compression offers better image quality especially when high compression is required.