Film grain noise modeling in advanced video coding
Byung Tae Oh, C.‐C. Jay Kuo, Shijun Sun, Shawmin Lei · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
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.