Skip to Main Content
A combined spatial- and temporal-domain wavelet shrinkage algorithm for video denoising is presented in this paper. The spatial-domain denoising technique is a selective wavelet shrinkage method which uses a two-threshold criteria to exploit the geometry of the wavelet subbands of each video frame, and each frame of the image sequence is spatially denoised independently of one another. The temporal-domain denoising technique is a selective wavelet shrinkage method which estimates the level of noise corruption as well as the amount of motion in the image sequence. The amount of noise is estimated to determine how much filtering is needed in the temporal-domain, and the amount of motion is taken into consideration to determine the degree of similarity between consecutive frames. The similarity affects how much noise removal is possible using temporal-domain processing. Using motion and noise level estimates, a video denoising technique is established which is robust to various levels of noise corruption and various levels of motion.