Paper Info
Title
An Improved Fuzzy Image Enhancement Algorithm
Abstract
An effective method for fuzzy image enhancement was presented by Russo, which was controlled by tuning of one parameter. The fixed parameter was used for the entire image resulting in over blurring or sharpening of image features in some parts of the image. On the basis of these, in this paper, we applied Russo's algorithm on different kinds of noise and proposed an efficient method to obtain the parameter values adaptively. Firstly, each pixel went through a phase of smoothing and then followed by a phase of combining smoothing and sharpening; Secondly, to effectively enhance image, each pixel local feature was adaptively assigned different parameter values by evaluating pixel local features through a fuzzy membership function; Finally, compared with Russopsilas method and other methods, experimental results indicated that the proposed method could achieve better performance than traditional methods for the enhancement of images corrupted with impulse and Gaussian noise.
Year
DOI
Venue
2008
10.1109/FSKD.2008.399
FSKD
Keywords
Field
DocType
parameter values adaptively,fuzzy set theory,enhancement algorithm,different parameter value,smoothing methods,image blurring,image sharpening,entire image,fuzzy image enhancement algorithm,image feature,russo algorithm,pixel local feature,fuzzy membership function,feature extraction,fixed parameter,improved fuzzy image,fuzzy image enhancement,image smoothing,gaussian noise,efficient method,image enhancement,image pixel feature,effective method,manganese,pixel,noise reduction,image features,noise
Sharpening,Feature detection (computer vision),Computer science,Artificial intelligence,Pattern recognition,Feature (computer vision),Fuzzy logic,Algorithm,Feature extraction,Smoothing,Pixel,Gaussian noise,Machine learning
Conference
Volume
ISBN
Citations 
1
978-0-7695-3305-6
0
PageRank 
References 
Authors
0.34
8
3
Name
Order
Citations
PageRank
Liangrui Tang14019.00
Jing Zhang200.68
Bing Qi364.33