Novel region-based image compression method based on spiking cortical model

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 ef cient and novel chain code is employed. This scheme tries to nd 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.

A survey and evaluation of bior wavelet based compression techniques

“…A 151 dB High Dynamic Range CMOS Image Sensor Chip Architecture with tone mapping compression embedded in-pixel; in the proposed framework, in-pixel content-aware adaptive global tone mapping algorithm is studied and tone mapping curve on the compression function of illuminations is calculated using histogram (Vargas et al, 2015). Novel region-based image compression method based on spiking cortical model; in this proposed method the authors exploits irregular segmentation region coding based on spiking cortical model (Zhao and Ma, 2015). An efficient DCT-based image compression system based on Laplacian transparent composite model; in this paper the authors identify outlier coefficients using Laplacian transparent composite model for image compression system (Sun and Yang, 2015).…”