A Reducing Multi-Noise Contrast Enhancement Algorithm for Infrared Image
Changjiang Zhang, Xiaodong Wang, Haoran Zhang, Guojun Lv, Han Wei · 2006
A kind of infrared image contrast enhancement algorithm based on discrete stationary wavelet transform (DSWT) and nonlinear gain operator is proposed. Having implemented DSWT to an infrared image, de-noising is done by the method proposed in the high frequency sub-bands which are in the better resolution levels and enhancement is implemented by combining de-noising method with incomplete Beta transform (IBT) in the high frequency sub-bands which are the worse resolution levels. According to experimental results, the new algorithm can reduce effectively the correlative noise (1/f noise), additive Gauss white noise (AGWN) and multiplied noise (MN) in the infrared image while it also enhances the contrast of infrared image well. In visual quality, the algorithm is better than the traditional unshaped mask method (USM), histogram equalization method (HIS)