A comparative study of Different Denoising Techniques in Digital Image Processing

The quality of image usually depends on various factors including noise, light, and temperature. Noise has a decisive role in the image as it is constantly present in different digital images. Noise implication may present during the image coding, transmission and development process. Noise removal has become an eye-catching and dynamic field in the Image processing domain. There is a significant recent advance in filtering of different kinds of noises for digital image processing. In this paper the problem of de-blurring in the presence of various noises is studied. A comparison among various filtering techniques is made in the presence of different kinds of noises. The experiments show that the Adaptive filter method performance is appealing both visually and in terms of objective quality measures that as the color peak-signal-to-noise ratio (CPSNR) and the mean square error (MSE) for Gaussian noise, Speckle noise, Poisson noise, while median filter demonstrates the visual objectives for salt and pepper noise.