Paper Info
Title
A Classification Algorithm to Distinguish Image as Haze or Non-haze
Abstract
The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.
Year
DOI
Venue
2011
10.1109/ICIG.2011.22
ICIG
Keywords
Field
DocType
image visibility,eigenvalues,distingussish image state,classification algorithm,human visual system judge,batch processing,human visual system,eigen value,image state,suppotr vector machine,svm,image contrast,image classification algorithm,image classification,support vector machine,distinguish image,image dehazing,dark channel intensity,dark channel,eigenvalues and eigenfunctions,non-haze image,real-time processing,support vector machines,haze image,haze images,nonhaze images,histograms,real time processing,feature extraction,edge detection
Computer vision,Histogram,Visibility,Pattern recognition,Feature detection (computer vision),Computer science,Human visual system model,Support vector machine,Feature extraction,Artificial intelligence,Contextual image classification,Haze
Conference
ISBN
Citations 
PageRank 
978-0-7695-4541-7
4
0.42
References 
Authors
4
4
Name
Order
Citations
PageRank
Xiaoliang Yu171.56
Chuangbai Xiao24016.05
Mike Deng391.54
P. Li421428.84