Title :
Research on millimeter-wave image denoising method based on contourlet and compressed sensing
Author :
Han, Bo ; Xiong, Jintao ; Li, Liangchao ; Yang, Jianyu ; Wang, Zhimin
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
In this paper, we analyze the general properties of passive millimeter-wave (PMMW) imaging system, then the denoising principle of contourlet and compressed sensing is briefly described. With both denoising advantages of contourlet and compressed sensing, a PMMW image denoising algorithm is designed. And, in the process of compressed sensing denoising, a new type of observation matrix, which is called amplitude-matching variable density measurement matrix, is proposed utilizing the priority information of low-pass property of system. Experiments demonstrate that this improvement can eliminate the “scratches” parts which the contourlet denosing produces. PSNR of image is enhanced and subjective visual feeling of millimeter-wave image is obviously improved.
Keywords :
image coding; image denoising; matrix algebra; millimetre wave imaging; PMMW image denoising algorithm; PMMW imaging system; amplitude-matching variable density measurement matrix; compressed sensing denoising; contourlet denosing; contourlet sensing; denoising advantages; denoising principle; low-pass property; millimeter-wave image denoising method; observation matrix; passive millimeter-wave imaging system; Compressed sensing; Imaging; Millimeter wave technology; Noise; Noise reduction; Signal processing algorithms; Transforms; amplitude-matching variable density measurement matrix; compressed sensing denoising; contourlet denoising; passive millimeter-wave image;
Conference_Titel :
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-6892-8
Electronic_ISBN :
978-1-4244-6893-5
DOI :
10.1109/ICSPS.2010.5555429