Development of an algorithm for automatic construction of a computational procedure of local image processing, based on the hierarchical regression
Автор: Kopenkov Vasiliy Nikolaevich, Myasnikov Vladislav Valerievich
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений: Распознавание образов
Статья в выпуске: 5 т.40, 2016 года.
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In this paper, we propose an algorithm for the automatic construction (design) of a computational procedure for non-linear local processing of digital signals/images. The aim of this research is to work out an image processing algorithm with a predetermined computational complexity and achieve the best quality of processing on the existing data set, while avoiding a problem of retraining or doing with less training. To achieve this aim we use a local discrete wavelet transform for a preliminary image analysis and the hierarchical regression to construct a local image processing procedure on the basis of a training dataset. Moreover, we work out a method to decide whether the training process should be completed or continued. This method is based on the functional of full cross-validation control, which allows us to construct the processing procedure with a predetermined computational complexity and veracity, and with the best quality.
Local processing, hierarchical regression, computational efficiency, machine learning, precedent-based processing, functional of full cross-validation
Короткий адрес: https://sciup.org/14059610
IDR: 14059610 | DOI: 10.18287/2412-6179-2016-40-5-713-720
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