Optimize ASIC design by statistics analysis and fixed parameter for special-imagery compression

Medical imagery needs the function of lossless compression to minimize image size to facilitate transmitting and storage. With high-speed and high-efficiency characteristics, FELICS algorithm has potential capability to do this job well. The research in this paper is not only based on FELICS algorithm, but also explores a practical method of fixing one of FELICS´s dynamic parameters as constant to optimize its ASIC implementation for special medical imagery. That is, toggling this key parameter of Rice coding in FELICS to a fixed value is able to save chip´s hardware resources, like die area, power consumption and computational workload. More important in this process is applying statistics analysis on real images to choose the biggest-probability value for it. At last, the fixing-k method has been validated by excellent results.