Abstract:

To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model (ISRCS) is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.

Key words: data compaction and compression, image processing and computer vision, region-based image coding, neural network