Low light image enhancement with dual-tree complex wavelet transform

In low light condition, low dynamic range of the captured image distorts the contrast and results in high noise levels. In this paper, we propose an effective contrast enhancement method based on dual-tree complex wavelet transform (DT-CWT) which operates on a wide range of imagery without noise amplification. In terms of enhancement, we employ a logarithmic function for global brightness enhancement based on the nonlinear response of human vision to luminance. Moreover, we enhance the local contrast by contrast limited adaptive histogram equalization (CLAHE) in low-pass subbands to make image structure clearer. In terms of noise reduction, based on the direction selective property of DT-CWT, we perform content-based total variation (TV) diffusion which controls the smoothing degree according to noise and edges in high-pass subbands. Experimental results demonstrate that the proposed method achieves a good performance in low light image enhancment and outperforms state-of-the-art ones in terms of contrast enhancement and noise reduction.