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

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.

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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,  https://doi.org/10.2352/ISSN.2470-1173.2021.10.IPAS-238

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