In this paper, we present a denoising method of using multiple image composition based on the color transform of local color distribution of patches. In the method, the color of a guidance image is transformed so as to get close to a noisy input image by a patch-wise color transform. As a result, a noiseless image is obtained. Actually this method can be regarded as the generalized version of our previous method [1] and the guided filter [2], and gives improved images with more clear appearance. The existing methods have a restriction that a filter output form is expressed only by a linear transform, i.e., a first order polynomial. In this paper, we introduce a more general formula for this category of filtering with the guidance image. We deal with a quadratic formula for realizing more flexible transform instead of the previous linear transform, and moreover introduce more simple and flexible regularization.

In the guided filter that performs operations such as denoising and contrast correction with the help of a guide image, the positions of corresponding subjects need to be completely aligned, otherwise the misaligned regions in the output image are deteriorated by blur. In this paper, we propose a guided filter for images which include moving dynamic regions. Our filter uses correspondences of local covariance matrices instead of using the conventional pixel-topixel correspondences. In addition, we also propose a classification method to detect the dynamic regions by using the support vector machine. Combining two kinds of guided filters for static / dynamic regions, more natural resulting images are obtained.