The Fuzzy Nonlinear Enhancement Algorithm of Infrared Image Based on Curvelet Transform
Jingchao Zhao, Shiru Qu · Procedia Engineering · 2011
Considering the low contrast and strong noise and without obvious distinction between target and background of infrared images, an enhancement algorithm is proposed. Firstly, Curvelet transform is performed on the original infrared image, and nonlinear gain function is applied to enhance the image's global contrast in the low frequency sub-band, set different thresholds using fuzzy nonlinear operator to adjust high-frequency coefficients, which extracts multi-scale detail features of the image; finally, reconstruct the image through the inverse Curvelet transform. Compared with other several infrared image enhancement algorithms, experimental results demonstrate that the algorithm reduce the noise of original image and enhance target content information effectively, and can preserve more contour features of the image.