Gee-Hyuk Lee, Dong-Woo Kim, Sang-Baek Han, Soo-Yong Kim
Optical Engineering, Vol. 34, Issue 01, (January 1995) https://doi.org/10.1117/12.188320
TOPICS: Computer programming, Quantization, Image restoration, Image compression, Error analysis, Statistical modeling, Stochastic processes, Algorithm development, Edge detection, Statistical analysis
Most of the existing lossy encoding schemes rely on the stochastic image model with a spatially uniform correlation and show decreasing performance as sharp edge features increase in images. To cope with images where sharp edge features convey more important information, a relatively new encoding scheme utilizing a Laplacian edge detector is proposed and experimented with prototype sample images. In this scheme, the Laplacian operator is applied to an image to get a corresponding edge field and, in turn, the edge field is encoded with the Huffman code. A quantization, a fundamental information reduction step, is also carried out in the edge field, and the corresponding error field, the overall intensity variations, is approximated with some discrete sine transform coefficients. A compression ratio up to 5 or 6 can be achieved with the current implementation without a severe degradation of image quality. An implementation with an image divided into tiles and an extension to an hierarchical model will be studied in the future.