A new efficient method for color image compression based on visual attention mechanism

Abstract

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

A Computational Model for Landmarks Acquisition in Positioning

“…10.0 in dual-core PC with the CPU 2.8 GHz, memory 1.96 G. Firstly, extraction of feature points, generation of local saliency value, generation of integration saliency value and selection of attention points in the computational model are carried out by simulation. Then, the robustness of attention points and the vehicle's positioning performance when the attention points are used as landmarks are analyzed.…”

“…Let (x n mi , y n mi , z n mi ) (assuming it can be got by retrieving) be the landmarks' coordinate in global coordinate system. Then the distance r b m between the landmark iand the vehicle can be calculated, as shown in formula (10).…”

“…The research results show that: based on visual attention mechanism [8][9][10], the human brain is good for processing the information and finding the "significant" or "interesting" information. At the same time, other information which is less important is neglected.…”