Low lighting image enhancement using local maximum color value prior

摘要

We study the problem of low lighting image enhancement. Previous enhancement methods for images under low lighting conditions usually fail to consider the factor of image degradation during image formation. As a result, the lost contrast could not be recovered after enhancement. This paper will adaptively recover the contrast and adjust the exposure for low lighting images. Our first contribution is the modeling of image degradation in low lighting conditions. Then, the local maximum color value prior is proposed, i.e., in most regions of well exposed images, the local maximum color value of a pixel will be very high. By combining the image degradation model and local maximum color value prior, we propose to recover the un-degraded images under low lighting conditions. Last, an adaptive exposure adjustment module is proposed to obtain the final result. We show that our approach enables better enhancement comparing with popular image editing tools and academic algorithms.