Readability enhancement of low light images based on dual-tree complex wavelet transform

Since images captured under low light conditions have low dynamic range and are seriously degraded by noise, it is a challengeable task to achieve both contrast enhancement and noise reduction from low light images. In this paper, we propose a readability enhancement method of low light images based on dual-tree complex wavelet transform (DTCWT). We perform contrast enhancement and noise reduction for low light images based on wavelet coefficients. First, we conduct illumination compensation to contain fine details and fully utilize dynamic range. Then, we decompose the image into high-pass and low-pass sub-bands by DTCWT, and perform contrast limited adaptive histogram equalization (CLAHE) and a nonlinear transform in low-pass and high-pass sub-bands, respectively, to achieve both contrast enhancement and noise reduction. Finally, we perform color correction to deal with the color distortion problem caused by contrast enhancement. Experimental results demonstrate that the proposed method outperforms state-of-the-art ones in contrast enhancement, noise reduction, and color reproduction in terms of both subjective and objective evaluations.