Adaptive Object-Region-Based Image Pre-Processing for Noise Removal Algorithm

A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filte...

Full description

Saved in:
Bibliographic Details
Published in:KSII transactions on Internet and information systems 2013, 7(12), , pp.3166-3179
Main Authors: Ahn, Sangwoo, Park, Jongjoo, Luo, Linbo, Chong, Jongwha
Format: Article
Language:English
Subjects:
Algorithms
Image processing
Methods
Noise control
Visual perception
컴퓨터학
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filters can be applied to other regions to reduce overall computational complexity. In the proposed method, bright region segmentation is performed, followed by segmentation of object and background regions. Noise in dark, background, and object regions is then removed by the median, fast bilateral, and bilateral filters, respectively. Simulations show that the proposed algorithm is much faster than and performs nearly as well as the bilateral filter (which is considered a powerful noise removal algorithm); it reduces computation time by 19.4 % while reducing PSNR by only 1.57 % relative to bilateral filtering. Thus, the proposed algorithm remarkably reduces computation while maintaining accuracy. Keywords: noise reduction, image segmentation, bilateral filter, higher-order statistics, pre-processing
ISSN:1976-7277
1976-7277
DOI:10.3837/tiis.2013.12.012