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The development of modern technologies in the field of image formation leads to an increase in the size of the generated images, as a result the question of reducing the processing computational costs arises, and this is an important factor in the creation of real-time systems. The study provides a description of high-speed recursive-separable filters for improving the quality of images, which, due to the peculiarities of their implementation, can reduce the number of computational operations required for the image processing process. This type of filters is obtained from two-dimensional linear digital filters, which are modified by applying recursive and separable properties to them. The MATLAB environment computing method for implementation of these filters is described. An extensive performance research of the developed filters has been carried out at various sizes of the test image and on various experimental installations. The comparison with the classical two-dimensional convolution method of the developed filters is demonstrated, and it shows the time gain required for the image processing. The results obtained can be applied in biomedical image processing systems or in vision systems working in heavy weather conditions.
image processing, recursive-separable algorithms, computational costs reduction, computer vision.
Kamenskiy AV. High-speed recursive-separable image processing filters. Computer Optics 2022; 46(4): 659-665. DOI: 10.18287/2412-6179-CO-1063.
The research was carried out at the expense of the Russian Science Foundation grant No. 21-79-10200 at TUSUR.
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