RATE DISTORTION OPTIMIZATION FOR VIDEO DENOISING

摘要

Based on maximum a posteriori (MAP) estimates, video denoising techniques for frames of noisy video are provided. With the assumptions that noise is similar to or satisfies Gaussian distribution and an a priori conditional density model measurable by bit rate, a MAP estimate of a denoised current frame can be expressed as a rate distortion optimization problem. A constraint minimization problem based on the rate distortion optimization problem is used to vary a lagrangian parameter to optimize the denoising process. The lagrangian parameter is determined as a function of distortion of the noise.