High-fidelity adaptiv medical image reconstruction using realtime wavelet filter design for fast internet transmission and display

Most high resolution medical images such as X-ray radiographic images require enormous storage space and considerable time for transmission and viewing. We propose a wavelet design that creates the optimal filter taps for any class of images adaptively for high fidelity image reconstruction using an energy compacted section of the wavelet decomposed original image with considerable reduction in memory requirement as well as in execution, transmission, and viewing time. This optimal filter tap design is based on two-channel perfect reconstruction quadrature mirror filter (PR-QMF) banks using an interior-point-based optimization algorithm. The algorithm finds wavelet filter taps that allows the smallest amount of energy in the detail sections of the wavelet decomposition of an image in real time. Once the filter taps have been created and a one level wavelet transform has been performed, the energy compacted component of the image containing one fourth of the number of elements in the original image, is retained without any significant loss in the information content. This energy compacted section of the image is then used for any chosen advanced compression algorithm. This technique provides a significant reduction in execution time without an appreciable increase in distortion for advanced lossy image compression algorithms