The article considers the issue of using the multi-criteria smoothing method, with the possibility of adaptive parameter changes for various types of images. As an approach to implement the improvement of the group of images, the work proposes phased processing for each multi-channel image. As a first step, an algorithm for changing the color space is applied, in which multiple adaptive compression of the range occurs, based on a change in the size of the clusters. This algorithm allows adaptive absorption of adjacent pixel regions by analysis of histograms of the gradients. The application of this approach allows performing primary localization and simplification of the image. In the next step, we search for areas of significance (maximum number of transitions or complexity of an object). We check the coincidence of areas in a multi-channel image. Next, we perform image smoothing. As a filter mask, the data obtained at the previous stages of processing are used. The parameters of the multicriteria method depend on the value of a certain standard deviation coefficient and the analysis area (object boundary, detailed section, or locally stationary region). At the final stage, we perform an image enhancement operation based on the application of the α-rooting algorithm in local areas defined in the first stages of the algorithm. All operations are performed for each image in all the channels. The approach proposed in the article showed high efficiency and the possibility of applying for the processing of multichannel images. This is method can be expanded to other groups and types of sensors.
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