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On halting the process of hierarchical regression construction when implementing computational procedures for local image processing

  • Representation, Processing, Analysis and Understanding of Images
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Abstract

This paper considers the question of the use of the complete sliding control function when solving the problem of automatic construction of the local processing procedure of image signals adjusted using empirical data (hierarchical regression). A technique to halt the process of forming various combinations of training and control samples and, hence, the process of constructing the image processing procedure is proposed and based on an interval estimate of the functional of sliding quality control.

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Authors and Affiliations

  1. Image Processing Systems Institute, ul. Molodogvardeiskaya 151, Samara, 443001, Russia

    V. N. Kopenkov

Authors
  1. V. N. Kopenkov
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Correspondence to V. N. Kopenkov.

Additional information

This paper uses the materials of the report submitted at the 11th International Conference “Pattern Recognition and Image Analysis: New Information Technologies,” Samara, The Russian Federation, September, 23–28, 2013.

Vasilii Nikolaevich Kopenkov was born in 1978. He graduated from Samara State Aerospace University in 2001. He received his Candidate of Technical Sciences degree in 2011. At present, he is an associate professor and Geoinformatics and Information Security chair at Samara State Aerospace University and a researcher at the Image Processing Systems Institute, Russian Academy of Sciences. His scientific interests include digital image and signal processing, geoinformatics, pattern recognition, and earth remote sensing data processing. He is the author of 42 publications, including 14 articles. He is a member of the Russian Pattern Recognition and Image Analysis Association.

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Kopenkov, V.N. On halting the process of hierarchical regression construction when implementing computational procedures for local image processing. Pattern Recognit. Image Anal. 24, 506–510 (2014). https://doi.org/10.1134/S1054661814040087

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  • DOI: https://doi.org/10.1134/S1054661814040087

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