Adaptive Low-Light Image Enhancement with Decomposition Denoising

Noise in low-light image enhancement seriously affects human observation and computer vision algorithms, while existing methods inevitably introduce under- or over-contrast problems. We proposed an adaptive low-light image enhancement with decomposition denoising to perform a good visual effect. Firstly, the low-rank denoising algorithm is designed to decrease the noise of an input low-light image. And then, adaptive luminance enhancement is developed by generating a nonlinear function to improve the luminance of the denoise image. Finally, a color restoration method based on the relationship between spectral bands and input image into a color image. Subjective and objective experiments show that compared to several state-of-the-art methods, the proposed method can reasonably enhance image luminance and contrast while removing heavy noise.