Abstract: Noise removal in images is one of the most basic tasks of image processing. Algorithms for removing noises in image sequences aim to remove the additive noise while utilizing both the spatial and the temporal domains. Such an approach is expected to lead to a gain both in the denoising performance and the computational load when compared to applying a single image denoising algorithm to each image separately. We propose a new algorithm viterbi by considering 3-D (spatio-temporal) patches, a propagation of the +dictionary over time and averaging that is done on neighboring patches both in space and time. As the dictionary of adjacent frames is expected to be nearly identical, the number of required iterations per frame can be significantly reduced.
M. Sreedevi and P. Jenoaul, 2011. Additive White Gaussian Noise Removal Using Viterbi Algorithm. Asian Journal of Information Technology, 10: 119-121.