Tampere University of Technology

TUTCRIS Research Portal

Efficiency of texture image filtering and its prediction

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)1543–1550
Number of pages8
JournalSignal, Image and Video Processing
Issue number8
Publication statusPublished - 2016
Publication typeA1 Journal article-refereed


Textures are typical elements of natural scene images widely used in pattern recognition and image classification. Noise, often being present in acquired images, deteriorates texture features (characteristics), and it is desirable both to suppress it and to preserve a texture. This task is quite difficult even for the most advanced filters, and the resulting denoising efficiency can be quite low. Due to this, it is desirable to predict a denoising efficiency before filtering to decide whether it is worth filtering a given image or not. In this paper, we analyze several quantitative criteria (metrics) that can characterize filtering efficiency. Prediction strategy is described and its accuracy is studied. Several modern filtering techniques are analyzed and compared. Based on this, practical recommendations are given.


  • Filtering efficiency, Image enhancement, Noise suppression, Visual quality

Publication forum classification

Field of science, Statistics Finland