Film grain noise modeling in advanced video coding

Abstract

A new technique for film grain noise extraction, modeling and synthesis is proposed and applied to the coding of high definition video in this work. The film grain noise is viewed as a part of artistic presentation by people in the movie industry. On one hand, since the film grain noise can boost the natural appearance of pictures in high definition video, it should be preserved in high-fidelity video processing systems. On the other hand, video coding with film grain noise is expensive. It is desirable to extract film grain noise from the input video as a pre-processing step at the encoder and re-synthesize the film grain noise and add it back to the decoded video as a post-processing step at the decoder. Under this framework, the coding gain of the denoised video is higher while the quality of the final reconstructed video can still be well preserved. Following this idea, we present a method to remove film grain noise from image/video without distorting its original content. Besides, we describe a parametric model containing a small set of parameters to represent the extracted film grain noise. The proposed model generates the film grain noise that is close to the real one in terms of power spectral density and cross-channel spectral correlation. Experimental results are shown to demonstrate the efficiency of the proposed scheme.

Advanced Film Grain Noise Extraction and Synthesis for High-Definition Video Coding

“…It is worthwhile to point out that the median-based algorithm needs additional memory to store the signal distribution while the mean-based method can be performed without additional memory due to the dynamic updating process by specified in (6).…”

“…This process is similar to the overcomplete wavelet decomposition. In [6], we proposed to use a multiresolution overcomplete wavelet decomposition with simple integer-valued lowand high-pass filters. However, we found that its frequency selectivity is not good enough so that it could miss some signal with specific frequency bands.…”

“…Under the assumption that film grain noise is one of the Gaussian additive or multiplicative noise, many existing denoising methods could be used. However, this assumption does not hold since film grain noise has the following distinctive properties [1], [3], [4], [6], [7].…”

Enhanced Film Grain Noise Removal for High Fidelity Video Coding

“…Under the assumption that film grain noise is one of the Gaussian additive or multiplicative noise types, many existing denoising methods could be used. However, this assumption does not hold, since film grain noise has the following distinctive properties [1], [2], [3], [5], [6].…”

“…Therefore, film grain noise removal algorithms for high fidelity video coding have attempted to prevent distortion of the features of the underlying contents even if denoising is performed [5], [6], [7]. For this, Oh et al only adopted spatial denoising filtering, nonlinear total variation [8], for non-edge or non-texture regions [5], [6]. Although these methods preserve the edges and textures of the original image, the improvement in the coding efficiency is limited because the film grain noise still remains in the edge or texture region after denoising.…”