Low contrast image enhancement based on second generation curvelet transform
Xiaogang Chen · Computer Engineering and Applications Journal · 2008
A novel low contrast image enhancement approach based on the second generation curvelet is proposed.It overcomes the shortcomings of conventional methods,such as sensitively to noise and local over-enhancement.Firstly,the source image is decomposed by Curvelet transform.Then a kind of nonlinear enhancing function is applied to enhance the image’s global contrast in the low frequency subbands,and combining threshold denoising method with non-linear gain method to reduce the noise and enhance the details of image at each scale in the high frequency subbands.Finally,the enhanced coefficients are reconstructed to obtain enhanced image.Experimental results show that the proposed approach is superior to both histogram equalization and wavelet based contrast enhancement,it can preserve image edges and reduce the noise while enhancing contrast of the image,and also has good visual effect.