Infrared image nonlinear enhancement algorithm based on contourlet transform

Considering the low contrast and strong noise of infrared images, an infrared image nonlinear enhancement algorithm based on Contourlet transform is proposed. As an efficient directional multiresolution image representation method, Contourlet transform can offer different number of directions at different scales. Firstly, Contourlet transform is performed on the original infrared image at different scales and directions, thus the low frequency subband coefficients and varieties of directional bandpass subband coefficients are obtained. Then, incomplete beta function is applied to enhance the image's global contrast in the low frequency subband, and nonlinear gain function is used to process the coefficients at each scale in the directional bandpass subbands respectively, which suppresses small coefficients and enhances big coefficients by threshold denoising method. Finally, the enhanced infrared image is obtained by transforming these changed coefficients back to the spatial domain. The experimental results show that the algorithm proposed in this paper has advantages of enhancing low contrast infrared image efficiently over other methods, such as histogram equalization and wavelet transform enhancement. Our method can preserve more characteristics and reduce the noise of original image. It is superior to general histogram equalization and wavelet transform enhancement whatever in visual effect or in quantitative contrast parameter.