Wavelet-fractal based compression of ophthalmic image

This study is designed to determine the degree and methods of digital image compression to produce ophthalmic images of sufficient quality for transmission and diagnosis. Fractal based compression techniques, which provide a large compression ratio for grayscale images have been reported in the literature. Fractal coding is based on the fractal theory of iterated transformations. But, it's searching and mapping algorithm cannot address the need of real-time. To improve the real-time performance of the algorithm, we use wavelet transforms to decompose images. The wavelet transform is a natural tool for analyzing fractal block coders since wavelet bases possess the same type of dyadic self-similarity that fractal coders seek to exploit. We propose a method of fractal coding the weighted wavelet subtree. Experimented results show that the improved hybrid image can improve the PSNR of the rebuild image at the same compression ratio.