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Abstract

The processing of images to carry out specific features of an image is image enhancement. It is to develop an image so that the result is more appropriate than the original in definite application. During image acquisition, images are frequently degraded with noise due to imperfections in the imaging system. Images may lose important information that is required to enhance the quality of a given image. It is becoming quite difficult to extract right information from noisy images. Resolution and contrast are decisive attributes of a digital image. Now the question arises how to enhance the quality of a digital image so that it looks more pleading? The previous work which has been taken into the consideration and thus the simple DWT-HAAR method of resolution enhancement of the image is used. In this research work we develop a unique method for the image enhancement which would be a combination of wavelet transformation followed by the Neural Network. Wavelet transformation would be a result of two combinations namely Daubechies and Symlet. Now once the Daubechies and Symlet is combined, Neural Network has to be trained and on the basis of the training provided to the neural network the result would be evaluated that how much erosion has to be done in the image to enhance it. The evaluation parameters would be as PSNR, MSE and SNR. The results shows that neural network works better as compared to genetic algorithm when compared by given parameters results. The whole stimulation will take place in MATLAB 7.10 environment.

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Keywords

Image enhancement, Discreet Wavelet Transform, Neural network, Genetic algorithm, Noise.