Contrast Enhancement for Fruit Image by Gray Transform and Wavelet Neural Network
Changjiang Zhang, Xiaodong Wang, Haoran Zhang · 2006
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