A Traffic Image Compression Algorithm Based on Forecast and Quantization of Atomic Parameters
Long Liang-jiang · Journal of Highway and Transportation Research and Development · 2012
According to similar characteristics of background and local parts of traffic images,a traffic image compression algorithm based on forecast and quantization of atomic parameters was proposed to improve decoded image quality and vision impact at low bit-rates.The atomic dictionary was constructed by using the atomic parameters obtained from decomposition of traffic images.The forecast and quantization of atomic parameters was made by using the sparse decomposed atomic parameters.Then,projective components were arranged in order,subtracted and variable length coded.After that,atomic parameters were rearranged according to the rearranging order of projective components,and coded by arithmetic coding.Simulation results show that the algorithm can be more effective in the traffic image compression,and the image quality is better and has higher peak signal-to-noise ratio in the same compression ratio comparing with the method in the previous literatures.