Back to articles
Volume: 33 | Article ID: art00006
Benchmark of Similar Blocks Search under Noisy Conditions
  DOI :  10.2352/ISSN.2470-1173.2021.10.IPAS-238  Published OnlineJanuary 2021

A similarity search in images has become a typical operation in many applications. A presence of noise in images greatly affects the correctness of detection of similar image blocks, resulting in a reduction of efficiency of image processing methods, e.g., non-local denoising. In this paper, we study noise immunity of various distance measures (similarity metrics). Taking into account a wide variety of information content in real life images and variations of noise type and intensity. We propose a set of test data and obtain preliminary results for several typical cases of image and noise properties. The recommendations for metrics' and threshold selection are given. Fast implementation of the proposed benchmark is realized using CUDA technology.

Subject Areas :
Views 95
Downloads 0
 articleview.views 95
 articleview.downloads 0
  Cite this article 

Oleksii Rubel, Rostyslav Tsekhmystro, Vladimir Lukin, Karen Egiazarian, "Benchmark of Similar Blocks Search under Noisy Conditionsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems XIX,  2021,  pp 238-1 - 238-7,

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2021
Electronic Imaging
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane Springfield, VA 22151 USA