Result Analysis of Proposed Image Enhancement Algorithm Based on a Self Organizing Map Network and Wavelet Transform

Removing and reducing noise and improving the quality of image is very active research area in image processing. Various applications require various kinds of images as genesis of information for various works. Whenever an image is converted degradation occurs at the output. The output image processed through image enhancement for the removal of degradation. The main aim of Image enhancement is processing an image so the output result while be more suitable than the input image for specific task. Wavelet transforms have become one of the most important and powerful tool of signal representation. It has been used in image processing, enhancement, data compression, and signal processing. A processing of data through wavelet is very efficient in process of neural network. This paper is written for the discussion of the results which are obtained for proposed algorithm for image enhancement based on cascading of self organizing map network and wavelet transform which is compared to existing technique like histogram equalization, and multi point histogram equalization technique of image enhancement. The Self organizing map network is unsupervised training mechanisms of pattern, due to this reason the processing of network is very fast and efficient as compared to another artificial neural network technique. And the combination of wavelet and cascaded SOM network has a great advantage over conventional method such as histogram equalisation and multi-point histogram equalisation of image enhancement. Our experimental result shows that our proposed work performances better than the conventional method of image enhancement.