Image compression by vector quantization with noniterative derivation of acodebook: applications to video and confocal images

We demonstrate an image-compression technique that uses what we believe is a new noniterative codebook generation algorithm for vector quantization. T he technique supports rapid decompression and is equally applicable to indi vidual images or to a set of images without the need for interframe process ing. Compression with a single-image codebook is tested on (1) ten confocal images of the hindbrain of a mouse embryo, (2) video images of a polystyre ne microsphere that is manipulated by a focused laser light, and (3) five f luorescence images of the embryo eye lens taken at different magnifications . The reconstructions are assessed with the normalized mean-squared error a nd with Linfoot's criteria of fidelity, structural content, and correlation quality. Experimental results with single-image compression show that the technique produces fewer local artifacts than JPEG compression, especially with noisy images. Results with video and confocal image series indicate th at single-image codebook generation is sufficient at practical compression ratios for producing acceptable reconstructions for mouse embryo analysis a nd for viewing optically trapped microspheres. images also reveal that the compression scheme is robust to scaling. (C) 1999 Optical Society of Americ a. OCIS codes: 100.5010, 100.2000.