Preety D. Swami¹, Alok Jain¹ and Dhirendra K. Swami², ¹SATI, India and ²VNSIT, India

This paper proposes a neural network based region classification technique that classifies regions in an image into two classes: textures and homogenous regions. The classification is based on training a neural network with statistical parameters belonging to the regions of interest. An application of this classification method is applied in image denoising by applying different transforms to the two different classes. Texture is denoised by shearlets while homogenous regions are denoised by wavelets. The denoised results show better performance than either of the transforms applied independently. The proposed algorithm successfully reduces the mean square error of the denoised result and provides perceptually good results.

Classification, Image denoising, Neural Network, Shearlets, Wavelets