Film grain noise removal and synthesis in video coding

Dai, Jingjing; Au, Oscar C.; Pang, Chao; Yang, Wenxian; Zou, Feng

doi:10.1109/icassp.2010.5495254

Cited by 19 publications

(12 citation statements)

References 2 publications

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“…Gaussian. In [7], Dai et al reformulated MHMCF and extended it for film grain noise removal. In this section, we review the reformulation of MHMCF for film grain noise removal.…”

Section: A Reformulation Of Mhmcf For Film Grain Noise Removalmentioning

confidence: 99%

“…The proposed algorithm is tested with three digital camera sequences ("Freeway", "Plane" and "Waves"). We compare the proposed algorithm with the film grain noise removal based on MHMCF [7] applied in the RGB channels independently. Table II shows the denoising performance in digital camera sequences.…”

Section: A Denosing Performancementioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

“…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. To reduce the film grain noise in all regions while preserving edge information, Dai et al reduced film grain noise by using a multihypothesis motion compensated filter (MHMCF) [7]. As the MHMCF is a purely temporal filter, it can preserve most spatial details, and in particular, the edges remain sharp [9].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, film grain noise synthesis based on the autoregressive (AR) model has been proposed for high fidelity video coding [2], [3], [5], [6], [7]. These algorithms efficiently synthesize film grain noise in the decoder part.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Enhanced Film Grain Noise Removal for High Fidelity Video Coding

Hwang

Jeong

Choi

et al. 2013

2013 International Conference on Information Science and Cloud Computing Companion

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In this paper, we propose a novel technique for film grain noise removal, which can be adopted in high fidelity video coding. Film grain noise enhances the natural appearance of high fidelity video, therefore it is should be preserved. However, film grain noise is a burden to typical video compression systems because it has relatively large energy level in the high frequency region. In order to improve the coding performance while preserving film grain noise, the noise removal and synthesis process is used. We propose a film grain noise removal technology in the pre-processing step. In pre-processing step, film grain noise is removed by using temporal, spatial and inter-color correlation. Specially, color image denoisng using inter color prediction provides good denoising performance in noise concentrated B plane because film grain noise has inter-color correlation in the RGB domain. The results show that the coding gain of denoised video is higher than for previous works,while the visual quality of the final reconstructed video is well preserved.

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“…Gaussian. In [7], Dai et al reformulated MHMCF and extended it for film grain noise removal. In this section, we review the reformulation of MHMCF for film grain noise removal.…”

Section: A Reformulation Of Mhmcf For Film Grain Noise Removalmentioning

confidence: 99%

Section: A Denosing Performancementioning

confidence: 99%