PubMed · 9184892
A segmentation-based lossless image coding method for high-resolution medical image compression.
Abstract
Lossless compression techniques are essential in archival and communication of medical images. In this paper, a new segmentation-based lossless image coding (SLIC) method is proposed, which is based on a simple but efficient region growing procedure. The embedded region growing procedure produces an adaptive scanning pattern for the image with the help of a very-few-bits-needed discontinuity index map. Along with this scanning pattern, an error image data part with a very small dynamic range is generated. Both the error image data and the discontinuity index map data parts are then encoded by the Joint Bi-level Image experts Group (JBIG) method. The SLIC method resulted in, on the average, lossless compression to about 1.6 h/pixel from 8 b, and to about 2.9 h/pixel from 10 b with a database of ten high-resolution digitized chest and breast images. In comparison with direct coding by JBIG, Joint Photographic Experts Group (JPEG), hierarchical interpolation (HINT), and two-dimensional Burg Prediction plus Huffman error coding methods, the SLIC method performed better by 4% to 28% on the database used.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
L Shen, R M Rangayyan. 1997. A segmentation-based lossless image coding method for high-resolution medical image compression.. https://doi.org/10.1109/42.585764
Cite the original work for its findings. Save a collection to share your selection of sources.