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Linear operators with vector masks in digital image processing problems
A.I. Novikov 1, A.V. Pronkin 1

1 Ryazan State Radio Engineering University named after V.F. Utkin,
390005, Ryazan, Russia, Gagarina 59/1

 PDF, 773 kB

DOI: 10.18287/2412-6179-CO-1241

Pages: 596-604.

Full text of article: Russian language.

Abstract:
The paper shows that it is expedient to use vector masks for solving some types of digital image processing problems. The main advantage of vector masks compared to matrix masks is that they reduce the computational complexity of algorithms while maintaining, and in some problems even improving, quality indicators. The article demonstrates examples of the use of vector masks in the problem of estimating the level of discrete white noise in an image, forming a basis for constructing a correctly working sigma filter, which are used for obtaining smoothed partial derivative estimates in the problem of edge detection and detecting straight lines in a contour image. The work uses results obtained by the authors in their earlier publications.

Keywords:
linear operators, vector mask, convolution, noise variance estimation, edge detection, contour image, line detection.

Citation:
Novikov AI, Pronkin AV. Linear operators with vector masks in digital image processing problems. Computer Optics 2023; 47(4): 596-604. DOI: 10.18287/2412-6179-CO-1241.

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