Low-Cost Method of Noise Estimation for Image and Video Coding

Existing video and image codecs exploit spatial and temporal correlation to achieve compression, but presence of noise reduces this correlation and hence adversely effects their compression efficiency. Noise filtering of the input signal can significantly improve compression efficiency of video encoders. Temporal noise filtering is one such technique that can improve the compression efficiency of encoding noisy content by 5-10% with an AVI reference encoder. Temporal filtering relies on motion information and noise estimation for generating accurate filter coefficients. Generally, encoders have motion estimation modules which can be used for getting motion information, but noise estimation requires a special implementation. In this proposal, we present a low-cost noise estimation method which is used with temporal filtering in AV1 encoding. We calculate the difference between pixels in horizontal and vertical directions to generate the histograms of a difference map. A simple analysis of these histograms provides a very accurate measure of variance of the noise in frames. In comparison to the existing methods, this method has a very low computational overhead.