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. Kopenkova, V. V. Myasnikovab
a Samara National Research University, Samara, Russia
b Image Processing Systems Institute îf RAS, – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia
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.
|Russian Science Foundation
|This work was financially supported by the Russian Science Foundation (RSF), grant no. 14-31-00014 “Establishment of a Laboratory of Advanced Technology for Earth Remote Sensing”.
PDF file (456 kB)
V. N. Kopenkov, V. V. Myasnikov, “Development of algorithm for automatic construction of a computational procedure of local image processing, based on the hierarchical regression”, Computer Optics, 40:5 (2016), 713–720
Citation in format AMSBIB
\by V.~N.~Kopenkov, V.~V.~Myasnikov
\paper Development of algorithm for automatic construction of a computational procedure of local image processing, based on the hierarchical regression
\jour Computer Optics
Citing articles on Google Scholar:
Related articles on Google Scholar:
|Number of views:|