Title
Adaptive object-region-based image pre-processing for a noise removal algorithm
Abstract
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.
Year
DOI
Venue
2013
10.3837/tiis.2013.12.012
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Keywords
Field
DocType
noise reduction,image segmentation,bilateral filter,higher-order statistics,pre-processing
Noise reduction,Computer vision,Median filter,Segmentation,Computer science,Filter (signal processing),Algorithm,Image segmentation,Artificial intelligence,Bilateral filter,Computation,Computational complexity theory
Journal
Volume
Issue
ISSN
7
12
1976-7277
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
Sangwoo Ahn1103.19
Jongjoo Park252.50
Lin-bo Luo318915.97
Jong-Wha Chong412032.87