An Image Compression System With An HVS Model For Diagnostic Electron Microscopy
Kou-Hu Tzou, T.R. Hsing, Takashi Okagaki · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1985
Data Compression will reduce storage device problems and cut down the time required for transmission of high resolution medical images. In order to improve subjective image quality, various mathematical models of the human visual system (HVS) have been proposed for image compression applications. Most of these models are based upon data from psychophysical experiments on human vision. Since some nonlinear characteristics are involved in the human visual system, the psychophysically based model may not reflect the real HVS. In this paper, the physiologically based HVS model is incor-porated with the popular two-dimensional discrete cosine transform (DCT) coding to encode digitized images of diagnostic human tissue sections acquired by a scanning transmission electron microscopy (STEM). Simulation results are compared at 1 and 0.5 bit/pixel between systems with and without the HVS model. Superior subjective image quality was observed from the system with the HVS model. A study of coding scheme mismatch was also conducted to evaluate the robustness of DCT coding for medical image applications. Due to the strong similarity between the statistics of images, simulation results showed little degradation from coding scheme mismatch.