Digital Chest Image Compression Through Coding By Synthesis
Mike M. Tesic, Victor C. Chen, Karen L. Lauro · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1984
Clinical images obtained with an experimental digital chest system represent a unique image data base in that a large number of normal and abnormal chest images in digital format have been made available without the need to digitize films. The above image data base was used to measure certain characteristics of this class of images. Entropy and grey level histogram data and frequency spectrum statistical data were compiled for selected regions in the chest for the purpose of designing an effective image compression algorithm. By segmenting images into regions of high and low entropy, the former can be compressed in either a reversible or irreversible manner, while the latter are synthesized from knowledge of relatively few parameters in the process of displaying the image. The effect of compression ratio on image quality is assessed in a qualitative non-diagnostic manner, and it is found that significant compression can be achieved without objectionable degration of image information content with irreversible coding.