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Performance Analysis of Image Denoising Technique using Neural Network
| Content Provider | CiteSeerX |
|---|---|
| Author | Pathak, Shrish Kumar, Mukesh Saxena, Rohini |
| Abstract | Image processing is widely applied in various area of applications such as Medical, military, agriculture, etc.. The problem which generally occurs in image processing is the removal of noise generated due to various sources. In this paper a new approach based on neural network technique is proposed for the removal of noise. This technique follows three levels. This technique combines the advantages of filtering, neural network and bayes shrinkage technique. The noisy image is first passed through a bilateral filter and neural network is applied to the filtered image and the output of NN is then applied to bayes shrink. The proposed method outperforms other methods both visually and in case of objective quality peak-signal-to-noise ratio (PSNR) and MSE. Proposed method is verified for additive white Gaussian noise. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Neural Network Image Denoising Technique Performance Analysis Image Processing Objective Quality Peak-signal-to-noise Ratio Bayes Shrinkage Technique Various Source Various Area Additive White Gaussian Noise Noisy Image Neural Network Technique Bilateral Filter |
| Content Type | Text |
| Resource Type | Article |
