IMAGE SEQUENCE FILTERING ALGORITHMS FOR RESOLUTION IMPROVEMENT IN APPLICATIVE NOISE CONDITIONS
A. Yu. Ivankov, A. A. Sirota
Voronezh State University, Universitetskaya Ploshchad’ 1, Voronezh, 394006 Russia
Keywords: обработка изображений, сегментация, аппликативные помехи, суперразрешение, фильтр Калмана, image processing, segmentation, applicative noise, super resolution, the Kalman filter
Abstract
Algorithms for improving the resolution of a sequence of images distorted by applicative noise manifested in the form of randomly shaped local regions of occlusion are synthesized and analyzed. The basis is the implementation of an optimal linear filtering algorithm in block form, which is synthesized with account for possible emergence of false observations in individual elements of the analyzed images. A method for incorporating the results of independent segmentation of each individual image into the recursive filtering process is proposed, which enhances the quality of the final processing.
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