A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Measuring perceived quality of speech and video in multimedia conferencing applications
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Real-time texture synthesis by patch-based sampling
ACM Transactions on Graphics (TOG)
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Signal-dependent film grain noise removal and generation based on higher-order statistics
SPWHOS '97 Proceedings of the 1997 IEEE Signal Processing Workshop on Higher-Order Statistics (SPW-HOS '97)
Lossy compression of noisy images
IEEE Transactions on Image Processing
A perceptually lossless, model-based, texture compression technique
IEEE Transactions on Image Processing
A multiresolution approach for texture synthesis using the circular harmonic functions
IEEE Transactions on Image Processing
A deblocking algorithm for JPEG compressed images using overcomplete wavelet representations
IEEE Transactions on Circuits and Systems for Video Technology
A motion-compensated spatio-temporal filter for image sequences with signal-dependent noise
IEEE Transactions on Circuits and Systems for Video Technology
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A technique for film grain noise extraction, modeling and synthesis is studied and applied to high-definition video coding in this paper. Film grain noise enhances the natural appearance of pictures in high-definition video and should be preserved in coded video. However, the coding of video contents with film grain noise is expensive. In previous art, it was proposed to enhance the coding performance by extracting film grain noise from the input video at the encoder as a preprocessing step, and by resynthesizing and adding it back to the decoded video at the decoder as a postprocessing step. In a novel implementation of this approach, we first remove film grain noise from image/video with a variational denoising approach without distorting its original content. Then, we present a parametric model (consisting of a small set of parameters) to generate film grain noise that is close to the actual one in terms of a couple of observed statistical properties, such as the power spectral density and the crosschannel spectral correlation. Under this framework, the coding gain of denoised video is higher while the visual quality of the final reconstructed video is well preserved. Experimental results are provided to demonstrate the superior performance of the proposed approach.