基于压缩感知的感兴趣区域编码

Region of Interest Coding Based on Compressed Sensing

受无线信道带宽的约束,图像经传统图像压缩方法压缩并经无线信道传输后,图像质量受损严重,会影响后续探测识别结果的准确性,本文针对这个问题提出一种基于压缩感知(Compressed Sensing,CS)的感兴趣区域(Region Of Interest,ROI)图像压缩方法。首先,将位平面位移技术引入压缩感知,对获得的图像进行量化、位平面分解;然后位移ROI位平面,并给出编码方案;最后,在解码端通过解码、重构,得到ROI质量良好的重构图像。仿真结果表明,本文算法重构图像的ROI部分PSNR高于传统的压缩感知编码方法,验证了方法的可行性和有效性,从而为ROI图像编码提供了一种可行的解决方案。

In order to solve the conflict between the requirement for high image quality for detection and recognition task and the constraint of wireless channel bandwidth,the paper proposes a ROI(Region of Interest)coding algorithm based on compressed sensing.Compressed sensing is employed to compress images due to its excellent anti-interference capability,and bit plane scaling technology is introduced into it.First,the blocked compressed sensing signals are quantified and decomposed to bit planes.Then,the bit planes of the region of interest are shifted.Finally after decoding,the high-quality reconstructed ROI image is achieved.Experimental results indicate that the PSNR of the reconstructed ROI part encoded through the bit plane shifting algorithm is higher than that through the traditional compressed sensing coding technology.Therefore the ROI coding algorithm based on compressed sensing can improve the efficiency of the wireless image transmission system,and meet the requirements of target detection and identification better.