Image noise level estimation by searching for smooth patches with discrete cosine transform
Hayato Katase, Takuro Yamaguchi, Takanori Fujisawa, Masaaki Ikehara · 2016
When denoising an image, noise level is one of the most vital input parameters, because setting wrong noise level affects a result of denoising. Therefore, the noise level must be estimated accurately. In this paper, we propose a new accurate noise level estimation method based on the characteristic of discrete cosine transform (DCT) coefficients. This characteristic is that the high-frequency coefficients of the smooth patches can be assumed to zero. We select smooth patches from a distribution of the standard deviation of high-frequency coefficients in a noisy image, and a distribution function of the standard deviation of high-frequency coefficients in an only noise image. Moreover, we propose a method that the estimated noise level is calculated from high-frequency coefficients in a noisy image. The experiment results with many images demonstrate that the proposed method estimates the noise levels more accurately, in comparison with the conventional methods.