基于改进的分块压缩感知红外图像重建

针对基于压缩感知理论的红外图像重建问题,提出一种基于改进的分块压缩感知红外图像重建方法。该方法首先对原始红外图像进行分块,并对每个子块用相同的观测矩阵进行随机观测,获得少量的观测数据;然后利用谱图小波变换优异的稀疏特性,将其引入平滑投影Landweber算法进行迭代优化重建,同时采用混合中值滤波进行处理以增加图像的平滑度和减少块伪影,最后输出满足要求的高质量红外图像。实验结果表明,在相同采样率下,该方法对于不同类型红外图像的重建性能均优于目前广为采用的一些小波压缩感知方法,可获得更高质量的红外图像。

Abstract

Regarding to the reconstruction problem of an infrared image in compressed sensing, we proposed a modified block compressed sensing method. First, the original infrared image is divided into small blocks, each of which is sampled with a Gaussian random matrix to generate a small amount of measurement data. Second, Spectral Graph Wavelet transform with excellent sparse features is applied into reconstruction process of projected Landweber algorithm, and the hybrid median filter is used for enhancing image smoothness and reducing block artifacts. Finally, the high-quality infrared image satisfied termination conditions is obtained. Experimental results on various types of infrared images show that the proposed method attains much better performance in CS recovery than the conventional ones and can obtain higher quality infrared images.

参考文献

[1] 范晋祥, 杨建宇. 红外成像探测技术发展趋势分析[J]. 红外与激光工程, 2012, 41(12): 3145-3153.(Fan Jinxiang, Yang Jianyu. Development trends of infrared imaging detecting technology. Infrared and Laser Engineering, 2012, 41(12): 3145-3153)

[2] Donoho D L. Compressed sensing[J]. IEEE Trans on Information Theory, 2006, 52(4): 1289-1306.

[3] 齐聪慧, 赵志钦, 徐晶, 等. 复杂场景下基于压缩感知的目标电磁散射与成像[J]. 强激光与粒子束, 2014, 26: 073206.(Qi Conghui, Zhao Zhiqin, Xu Jing, et al. Electromagnetic scattering and image processing of target under complex environment based on compressive sensing method. High Power Laser and Particle Beams, 2014, 26: 073206)

[4] 张桂珊, 肖刚, 戴卓智, 等. 压缩感知技术及其在MRI上的应用[J]. 磁共振成像, 2013, 4(4): 314-320.(Zhang Guishan, Xiao Gang, Dai Zhuozhi, et al. Compressed sensing technology and its application in MRI. Chinese Journal of Magnetic Resonance Imaging, 2013, 4(4): 314-320)

[5] 古宇飞, 闫镔, 王彪, 等. 结合透射CT的康普顿背散射图像重建[J]. 强激光与粒子束, 2014, 26:024003.(Gu Yufei, Yan Bin, Wang Biao, et al. Compton scattering tomography reconstruction algorithm combined with transmission CT. High Power Laser and Particle Beams, 2014, 26:024003)

[6] Willett R M, Marcia R F, Nichols J M. Compressed sensing for practical optical imaging systems: a tutorial[J]. Optical Engineering, 2011, 50: 072601.

[7] Lu Gan. Block compressed sensing of natural images[J]. IEEE International Conference on Digital Signal Processing, 2007(15): 403-406.

[8] Mun S, Fowler J E. Block compressed sensing of images using directional transforms[J]. IEEE International Conference on Image Processing, 2009(16): 3021-3024.

[9] Hammond D K, Vandergheynst P, Gribonval R. Wavelets on graphs via spectral graph theory[J]. Applied and Computational Harmonic Analysis, 2011, 30(2): 129-150.

[10] Van Trinh C, Dinh K Q, Jeon B. Edge-preserving block compressive sensing with projected landweber[C]//Systems, Signals and Image Processing(IWSSIP), 20th International Conference on IEEE. 2013: 71-74.

[11] Gómez de Dueas S. Long exposure video-surveillance: isolation of new object on the scenario and rejection of detection due to movement of background objects[D]. Italy: Politecnico di Milano, 2010: 18-19.

[12] 叶双清, 杨晓梅. 基于小波变换和非局部平均的超分辨率图像重建[J]. 计算机应用, 2014, 34(4): 1182-1186.(Ye Shuangqing, Yang Xiaomei. Super resolution image reconstruction based on wavelet transform and non-local means. Journal of Computer Applications, 2014, 34(4): 1182-1186)

秦翰林, 韩姣姣, 延翔, 周慧鑫, 李佳, 曾庆杰. 基于改进的分块压缩感知红外图像重建[J]. 强激光与粒子束, 2014, 26(12): 121011. Qin Hanlin, Han Jiaojiao, Yan Xiang, Zhou Huixin, Li Jia, Zeng Qingjie. Infrared image reconstruction based on a modified block compressed sensing[J]. High Power Laser and Particle Beams, 2014, 26(12): 121011.

基于改进的分块压缩感知红外图像重建

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