DocumentCode
2397231
Title
Contrast Enhancement for Fruit Image by Gray Transform and Wavelet Neural Network
Author
Zhang, Changjiang ; Wang, Xiaodong ; Zhang, Haoran
Author_Institution
Coll. of Inf. Sci. & Eng., Zhejiang Normal Univ., Jinhua
fYear
0
fDate
0-0 0
Firstpage
1064
Lastpage
1069
Abstract
A new contrast enhancement algorithm for fruit image is proposed by gray transform and wavelet neural network (WNN). IBT is used to obtain non-linear gray transform curve. A new criterion is proposed with gray level histogram. Contrast type for original image is determined employing the new criterion. Transform parameters are determined directly by different contrast type of input image. In order to calculate non-linear gray transform in the whole image, a kind of WNN is proposed to approximate it. Experimental results show that the new algorithm is able to adaptively enhance the contrast for the image. The computation for the new algorithm is O (MN), where M and N are width and height in the original image
Keywords
image enhancement; image resolution; neural nets; wavelet transforms; contrast enhancement algorithm; fruit image; gray level histogram; incomplete beta transform; nonlinear gray transform curve; wavelet neural network; Histograms; Image converters; Image edge detection; Image enhancement; Image sequences; Information science; Infrared imaging; Neural networks; Shape; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
Conference_Location
Ft. Lauderdale, FL
Print_ISBN
1-4244-0065-1
Type
conf
DOI
10.1109/ICNSC.2006.1673299
Filename
1673299
Link To Document