Infrared Imaging Based on Compressive Sensing for Power Equipment Inspection
Infrared thermal imager has been broadly applied in power inspection. To increase the system quality, the target information should be obtained with as little as possible data. To obtain the target information by infrared imager with less data, a framework based on compressive sensing was studied here. By projecting the original target to a sparse space using wavelet transform, the target information can be represented sparsely. The measure matrix was constructed using Gaussian random distribution to position the sparse of the original target. An improved orthogonal matching pursuit algorithm was used to reconstruct the original target from the measurements. So a high resolution infrared image can be obtained by less linear measurements sampled by low resolution sensor. The results on several typical infrared targets of power inspection show that super-resolution infrared imaging can be realized by compressive sensing; the reconstructed images were precise enough compared with the original high resolution images. The mean square error between the reconstructed image and original image was low, and the PSNR is large.
power equipment inspection compressive sensing infrared image sparse orthogonal matching pursuit
Jianwei Ma Xiaomei Chi Jingtao Huang
Electronic and Information Engineering College Henan University of Science and Technology Luoyang China
国际会议
秦皇岛
英文
307-311
2010-11-05（万方平台首次上网日期，不代表论文的发表时间）