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Noise residual learning for noise modeling in distributed video coding
2012 Picture Coding Symposium, 2012Distributed video coding (DVC) is a coding paradigm which exploits the source statistics at the decoder side to reduce the complexity at the encoder. The noise model is one of the inherently difficult challenges in DVC. This paper considers Transform Domain Wyner-Ziv (TDWZ) coding and proposes noise residual learning techniques that take residues from ...
Huynh Van Luong, Søren Forchhammer
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Noise Power Estimation for Effective De-Noising in a Video Encoder
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006This paper presents a noise estimation algorithm using multiresolution motion estimation in a video encoder. Firstly, the motion estimator finds minimum block-matching errors at the finest resolution and the middle resolution for each macroblock. Secondly, if the minimum block-matching error at the finest resolution of a certain macroblock is less than
Byung Cheol Song, Kang Wook Chun
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Compression noise based video forgery detection
2014 IEEE International Conference on Image Processing (ICIP), 2014Intelligent video editing techniques can be used to tamper videos such as surveillance camera videos, defeating their potential to be used as evidence in a court of law. In this paper, we propose a technique to detect forgery in MPEG videos by analyzing the frame's compression noise characteristics.
Hareesh Ravi +3 more
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Comfort noise for compressed video
2005 Digest of Technical Papers. International Conference on Consumer Electronics, 2005. ICCE., 2005Similar to adding a dither signal to still images to hide contouring, a dither signal may be added to decompressed video prior to display to hide video compression artifacts such as blockiness. We propose that the added "comfort noise" be temporally correlated to reduce the perceived noisiness.
J.M. Boyce, A.M. Tourapis
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Noise measurement in video images
2000 Digest of Technical Papers. International Conference on Consumer Electronics. Nineteenth in the Series (Cat. No.00CH37102), 2002Many image enhancement algorithms easily fail in the presence of noise. Noise adaptive algorithms are much more robust, and a good and accurate enough algorithm for noise measurement is a key component. The proposed algorithms combine good performance with low complexity.
C. Hentschel, null Haiyan He
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Modeling of Surveillance Video Noise
Signal Processing, Pattern Recognition, and Applications / 722: Computer Graphics and Imaging, 2011This paper aims at breaking new ground in modeling and estimation of recording noise of surveillance video for further development of new techniques to restore video images. In order to tackle the video denoising problem with non-stationary image contents and various noise sources, a critical task is estimation of varieties of noise in video signals ...
Zhengya Xu +3 more
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Differential Video Noise Estimation
2006 International Conference on Communication Technology, 2006In this paper, we propose a fast and reliable white- noise variance estimation. The method subtracts two sequential frames of video first and then finds intensity-homogeneous blocks in both original image and differential image, and at last estimates the noise variance in these blocks by a Gaussian weighted averaging process.
Zhu Lei, Xu Peixia
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A Note on Video Noise Weighting
IEEE Transactions on Broadcasting, 1964A dicussion on video noise weighting is presented. A standard way of comparing results is proposed.
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Video De-noising by Different filters for different Noise
2018In this paper we have adopted various filter technique for removing noise from video. The existence of noise in video gives blurred, snowy appearance. Video contain noise that comes from different electronic sources. Noise reduction is a useful tool to: enhance perceptual quality, increase compression effectiveness, in addition to pattern recognition ...
Shree, Nidhi, Mathur, Swati
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Measuring noise correlation for improved video denoising
2012 19th IEEE International Conference on Image Processing, 2012The vast majority of previous work in noise reduction for visual media has assumed uncorrelated, white, noise sources. In practice this is almost always violated by real media. Film grain noise is never white, and this paper highlights that the same applies to almost all consumer video content.
Anil C. Kokaram +3 more
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