DocumentCode :
2338735
Title :
A new method for foggy image enhancment
Author :
Feng, Yan ; He, Mingyi ; Liu, Weihua
Author_Institution :
Shaanxi Key Lab. of Inf. Acquisition & Process., Northwestern Polytech. Univ., Xi´´an
fYear :
2009
fDate :
25-27 May 2009
Firstpage :
2416
Lastpage :
2419
Abstract :
As a common natural phenomenon, fog makes photographed images blurred, thus bringing great difficulty for monitoring of outdoors image, target identification and tracking and so on. In this paper, the authors propose a new method for foggy image enhancement that integrates multilevel wavelet decomposition, the auto-adapted LUM filter, soft threshold and so on. Firstly, carry on the multilevel wavelet decomposition to the image, and then obtain the low-frequency component and high-frequency components of image, use the auto-adapted LUM filter to low-frequency component, while utilize soft threshold based on Bayes estimation to process high-frequency components, and eventually carry on wavelet restructuring to the processed components. Through simulation, this method is proved to be superior to traditional methods in foggy image enchantment.
Keywords :
Bayes methods; filtering theory; fog; image enhancement; image reconstruction; image segmentation; target tracking; wavelet transforms; Bayes estimation; autoadapted LUM filter; foggy image enhancement; image blurring; multilevel wavelet decomposition; natural phenomenon; outdoor image monitoring; soft threshold; target identification; tracking method; wavelet restructuring; Atmospheric modeling; Filters; Frequency domain analysis; Helium; Image enhancement; Smoothing methods; Space technology; Target tracking; Wavelet analysis; Wavelet domain; autoadapted LUM filter; image enhancing; threshold process; wavelet decompose;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
Type :
conf
DOI :
10.1109/ICIEA.2009.5138634
Filename :
5138634
Link To Document :
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