This article is cited in 6 papers

IMAGE PROCESSING, PATTERN RECOGNITION

Development of algorithm for automatic construction of a computational procedure of local image processing, based on the hierarchical regression

V. N. Kopenkov^a, V. V. Myasnikov<sup>ab

a</sup> Samara National Research University, Samara, Russia
^b Image Processing Systems Institute оf RAS, – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

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.

Received: 26.09.2016
Accepted: 19.10.2016

Language: English

DOI: 10.18287/2412-6179-2016-40-5-713-720