Analysis on spectral effects of dark-channel prior for haze removal
In solving the inverse problem of haze removal, the most commonly used prior in the literature is perhaps that of dark channel, which assumes that at least one pixel in a small patch has a zero or near zero intensity level in one of the RGB color channels. However, this assumption is not physically based; it can be significantly off from the reality because most colors in outdoor natural scenes are unsaturated (e.g., the sky). Chances are that none of the R, G, B values in a patch of the latent image is close to zero. This paper offers detailed analysis on the effects of invalid dark channel assumption on dehazed images; in particular, it reveals the causes and behavior of spectral distortions that are inherent to the dark channel type of dehazing methods.