Comparative Result Analysis of Novel Algorithm based on RBF Network for Image Enhancement
Shobhit Verma, Hitesh Gupta
Abstract
Image Enhancement is for Improving Visibility and can also be used for different task, It is also important to provide a better representation for further automated image processing such as image analysis, detection, segmentation, recognition and data hiding which can be gain by image enhancement technique there are various method are available for the enhancement like histogram equalization etc in this paper we discuss the proposed algorithm for image enhancement based on RBF network and wavelet transform and also in this paper a comparative study has also done with cascaded SOM Network, HE, and MHE. The RBF Network is a local approximation three-layer feed forward neural network using a supervised training algorithm. It is much better than the regular BP network in approximation ability, classification ability and learning speed due to this reason the processing of network is very fast in compression of another artificial neural network method. And the combination of wavelet and RBF network has great advantage over conventional method.
Keyword
Image Enhancement, Wavelet, Neural Network, AMBE, PSNR, SOM, RBF, Histogram.