Adaptive Infrared Image Enhancement by Combining Differential Evolution with Stationary Wavelet Transformation
Chang Jiang Zhang, Yan Ling Zhou · Applied Mechanics and Materials · 2011
Considering noise and low contrast of infrared image，an efficient nonlinear adaptive enhancement algorithm，which is based on differential evolution (DE)algorithm and stationary wavelet transform (SWT)，is proposed. Evaluation function is constructed by combing information entropy，signal-noise-ratio with standard deviation of enhanced image. A nonlinear transformation function is designed to enhance the contrast of the infrared image. The optimal transformation parameters are determined by combing DE algorithm with the constructed evaluation function. The proposed algorithm can efficiently enhance the contrast of the infrared image while have a good robust to noise. Experimental results show that the proposed algorithm is better than multi-scale nonlinear enhancement algorithm，stationary wavelet nonlinear enhancement algorithm and histogram equalization algorithm in overall performance.