Image Denoising Using Cloud Model Filter

Image processing is the way of making the digital image to resemble the original image. It can be achieved by identifying the pixels that are different from the original image and then correcting the pixels to the required intensity. It is observed that techniques which follow the two stage process of detection of noise and filtering of noisy pixels achieve better performance than others. Classification is used to separate uncorrupted pixels from corrupted pixels. Reconstruction involves replacing the corrupted pixels by certain approximation technique. The performance of the proposed Cloud Model Filter is measured using the Peak Signal to Noise Ratio (PSNR) values. The PSNR values obtained for the restored image using the proposed filter is compared with the median filter. The performance of the filter is tested by taking various combinations of noisy images and varying the noise levels from 1percent to 100 percent. With any combination of noises, the proposed filter’s performance proved better than the median filter.