Wavelet Transform Based Image Denoising Using Spatial Adaptive Thresholding

In the modern age Visual information can be transmitted over communication channel in the type of digital images is decent method but after transmission corrupted image is found with noise. Before it can be used in applications we need to remove noise and reconstruct the image. Image denoising is the method to manipulate the image data and generate a high quality visual image. In this thesis we described image denoising using wavelet transform and various existing algorithms using different technique. The process of removing noise from an image is called as noise reduction or denoising. So we can introduce some significant wavelet transforms for image denoising such as VisuShrink BayesShrink and Bilateral thresholding and Proposed Spatial Adaptive thresholding techniques.