V.N. Kopenkov, V.V. Myasnikov

Samara National Research University, Samara, Russia

Full text of article: English language.

Abstract**:**

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.

Keywords:

local processing, hierarchical regression, computational efficiency, machine learning, precedent-based processing, functional of full cross-validation.

Citation:

Kopenkov VN, Myasnikov VV.** **Development of an algorithm for automatic construction of a computational procedure of local image processing, based on the hierarchical regression. Computer Optics 2016; 40(5): 713-720. DOI: 10.18287/2412-6179-2016-40-5-713-720.

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