| Digital images are widely used in computer applications. Uncompressed digital images require considerable storage capacity and transmission bandwidth. Efficient image compression solutions are becoming more critical with the recent growth of data intensive, multimedia-based web applications.; This thesis studies image compression using wavelet transforms and vector quantization. As a necessary background, the basic concepts of graphical image storage and currently used compression algorithms are discussed. The mathematical properties of several types of wavelets, including Haar, Daubechies, and biorthogonal spline wavelets are covered. This code implements a wavelet transform based image coder for gray scale images in MATLAB. A biorthogonal filter is used and the concept of symmetric extension is applied in image compression. Peak signal to noise ratio is computed. |
