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Q-STAR:A Perceptual Video Quality Model Considering Impact of Spatial, Temporal, and Amplitude Resolutions  [PDF]
Yen-Fu Ou,Yuanyi Xue,Yao Wang
Computer Science , 2012,
Abstract: In this paper, we investigate the impact of spatial, temporal and amplitude resolution (STAR) on the perceptual quality of a compressed video. Subjective quality tests were carried out on a mobile device. Seven source sequences are included in the tests and for each source sequence we have 27 test configurations generated by JSVM encoder (3 QP levels, 3 spatial resolutions, and 3 temporal resolutions), resulting a total of 189 processed video sequences (PVSs). Videos coded at different spatial resolutions are displayed at the full screen size of the mobile platform. Subjective data reveal that the impact of spatial resolution (SR), temporal resolution (TR) and quantization stepsize (QS) can each be captured by a function with a single content-dependent parameter. The joint impact of SR, TR and QS can be accurately modeled by the product of these three functions with only three parameters. We further find that the quality decay rates with SR and QS, respectively are independent of TR, and likewise, the decay rate with TR is independent of SR and QS, respectively. However, there is a significant interaction between the effects of SR and QS. The overall quality model is further validated on five other datasets with very high accuracy. The complete model correlates well with the subjective ratings with a Pearson Correlation Coefficient (PCC) of 0.991.
Temporal Resolution Enhancement in Compressed Video Sequences  [cached]
Robert L. Stevenson,Mark A. Robertson
EURASIP Journal on Advances in Signal Processing , 2001, DOI: 10.1155/s1687617201000269
Abstract: Compressed video may possess a number of artifacts, both spatial and temporal. Spatial compression artifacts arise as a result of quantization of the transform-domain coefficients, and are often manifested as blocking and ringing artifacts. Temporal limitations in compressed video occur when the encoder, in an effort to reduce bandwidth, drops frames. Omitting frames decreases the reconstructed frame rate, which can cause motion to appear jerky and uneven. This paper discusses a method to increase the frame rate of video compressed with the DCT by inserting images between received frames of the sequence. The Bayesian formulation of the restoration prevents spatial compression artifacts in the received frames from propagating to the reconstructed frames.
S. Suma Christal Mary M.E
International Journal on Computer Science and Engineering , 2010,
Abstract: In this paper propose a new method for the real-time hiding of information used in compressed video bitstreams. This method is based on the real-time hiding of information in audio steganography. This method of steganography is very similar to the two discussions ofimage steganography and video steganography. A new compressed video secure steganography(CVSS) algorithm is proposed. In this algorithm, embedding and detection operations are both executed entirely in the compressed domain, with no need for the decompression process. Thenew criteria employing statistical invisibility of contiguous frames is used to adjust the embedding strategy and capacity, which increases the security of proposed algorithm. Therefore, the collusion resistant properties are obtained. Video steganalysis with closed loop feedback manner is design as a checker to find out obvious bugs.
Distributed Compressed Video Sensing in Camera Sensor Networks  [PDF]
Yu Liu,Xuqi Zhu,Lin Zhang,Sung Ho Cho
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/352167
Abstract: With the booming of video devices ranging from low-power visual sensors to mobile phones, the video sequences captured by these simple devices must be compressed easily and reconstructed by relatively more powerful servers. In such scenarios, distributed compressed video sensing (DCVS), combining distributed video coding (DVC) and compressed sensing (CS), is developed as a novel and powerful signal-sensing and compression algorithm for video signals. In DCVS, video frames can be compressed to a few measurements in a separate manner, while the interframe correlation is explored by the joint recovery algorithm. In this paper, a new DCVS joint recovery scheme using side-information-based belief propagation (SI-BP) is proposed to exploit both the intraframe and interframe correlations, which is particularly efficient over error-prone channels. The DCVS scheme using SI-BP is designed over two frame signal models, the mixture Gaussian (MG) model and the wavelet hidden Markov tree (WHMT) model. Simulation results evaluated on two video sequences illustrate that the SI-BP-based DCVS scheme is error resilient when the measurements are transmitted through the noisy wireless channels. 1. Introduction Current video coding paradigms, such as MPEG and the ITU-T H.26x, are traditionally designed for the applications followed the so-called “broadcast” model, as shown in the left part of Figure 1. The video sequence is complicatedly encoded at the powerful server only once, and then the compressed video stream is distributed and decoded frequently on many cheap and simple user devices. So MPEG and H.26x standards both have complicated encoder and light decoder. Figure 1: The comparison of the “Broadcast” model and the “Multiple-access” model. However, with the booming of video devices ranging from low-power visual sensors to camera mobile phones, visual applications now have already developed beyond this broadcast model. The video processing paradigm in camera sensor networks, which are composed of spatially distributed smart camera devices capable of processing images or videos of a scene from a variety of viewpoints, is more like a “multiple-access” model, as shown in the right part of Figure 1. In this scenario, these video devices with limited battery power and storage memory need to send their captured video streams to the monitor server. Meanwhile, high compression efficiency is also required considering both the limitations of wireless bandwidth and transmission power. The requirements of the video processing paradigms here are diametrically opposed to MPEG and
New Hybrid Error Concealment for Digital Compressed Video  [cached]
Hadar Ofer,Huber Merav,Huber Revital,Greenberg Shlomo
EURASIP Journal on Advances in Signal Processing , 2005,
Abstract: Transmission of a compressed video signal over a lossy communication network exposes the information to losses and errors, which leads to significant visible errors in the reconstructed frames at the decoder side. In this paper we present a new hybrid error concealment algorithm for compressed video sequences, based on temporal and spatial concealment methods. We describe spatial and temporal techniques for the recovery of lost blocks. In particular, we develop postprocessing techniques for the reconstruction of missing or damaged macroblocks. A new decision support tree is developed to efficiently choose the best appropriate error concealment method, according to the spatial and temporal characteristics of the sequence. The proposed algorithm is compared to three error concealment methods: spatial, temporal, and a previous hybrid approach using different noise levels. The results are evaluated using four quality measures. We show that our error concealment scheme outperforms all the other three methods for all the tested video sequences.
A Compressed Video Steganography using TPVD
Sherly A P,Amritha P P
International Journal of Database Management Systems , 2010,
Abstract: Steganography is the art of hiding information in ways that avert the revealing of hidingmessages. This paper proposes a new Compressed Video Steganographic scheme. In thisalgorithm, data hiding operations are executed entirely in the compressed domain. Here data areembedded in the macro blocks of I frame with maximum scene change and in block of P and Bframes with maximum magnitude of motion vectors. To enlarge the capacity of the hiddensecret information and to provide an imperceptible stego-image for human vision, a novelsteganographic approach called tri-way pixel-value differencing (TPVD) is used for embedding.In this scheme all the processes are defined and executed in the compressed domain. Thoughdecompression is not required. Experimental results demonstrate that the proposed algorithmhas high imperceptibility and capacity.
Video Enhancement from Multiple Compressed Copies in Transform Domain  [cached]
Nguyen VietAnh,Chen Zhenzhong,Tan Yap-Peng
EURASIP Journal on Image and Video Processing , 2010,
Abstract: Increasingly, we can obtain more than one compressed copy of the same video content with different levels of visual quality over the Internet. As the original source video is not always available, how to choose or derive a video of the best quality from these copies becomes a challenging and interesting problem. In this paper, we address this new research problem by blindly enhancing the quality of the video reconstructed from such multiple compressed copies. The aim is to reconstruct a video that achieves a better quality than any of the available copies. Specifically, we propose to reconstruct each coefficient of the video in the transform domain by using a narrow quantization constraint set derived from the multiple compressed copies together, using a Laplacian or Cauchy distribution model for each AC transform coefficient to minimize the distortion. Analytical and experimental results show the effectiveness of the proposed method.
Hybrid-Based Compressed Domain Video Fingerprinting Technique  [cached]
Abbass S. Abbass,Aliaa A. A. Youssif,Atef Z. Ghalwash
Computer and Information Science , 2012, DOI: 10.5539/cis.v5n5p25
Abstract: Video fingerprinting is a newer research area. It is also called “content-based video copy detection” or “content-based video identification” in literature. The goal is to locate videos with segments substantially identical to segments of a query video while tolerating common artifacts in video processing. Its value as a tool to curb piracy and legally monetize contents becomes more and more apparent in recent years with the wide spread of Internet videos through user generated content (UGC) sites like YouTube. Its practical applications to a certain extent overlap with those of digital watermarking, which requires adding artificial information into the contents. Fingerprints are compact content-based signature that summarizes a video signal or another media signal. Several video fingerprinting methods have been proposed for identifying video, in which fingerprints are extracted by analyzing video in both spatial and temporal dimension. However, these conventional methods have one resemblance, in which video decompression is still required for extracting the fingerprint from a compressed video. In practical, faster computational time can be achieved if fingerprint is extracted directly from the compressed domain. So far, too fewer methods are known to propose video fingerprinting in compressed domain. This paper presents a video fingerprinting technique that works directly in the compressed domain. Experimental results show that the proposed fingerprint is highly robust against most signal processing transformations.
Design of the Quantization Matrix in the Distributed Compressed Sensing Video Coding*  [PDF]
Yueyue Dai, Xinhua Rui, Xuanyu Zhao
Journal of Computer and Communications (JCC) , 2016, DOI: 10.4236/jcc.2016.45003

In the frame of compressed sensing distributed video coding, the design of the quantization matrix directly affects the reconstruction quality of the receiving terminal of the video. In this article, we present a new design method of the Gaussian quantization matrix adapting to the compressed sensing coding, for that the distribution of the parameters of the image is featured of the characteristic of approximately normal distribution after measured by compressive sensing. By this way, the parameters of a certain quantity of the image frames depending on the video sequences generated by the Gaussian quantization matrix possess certain adaptive capacity. By comparison with the plan of the traditional quantization, the quantization matrix presented in this article would improve the reconstruction quality of the video.

H.264/AVC Video Compressed Traces: Multifractal and Fractal Analysis  [cached]
Reljin Irini,Sam?ovi? Andreja,Reljin Branimir
EURASIP Journal on Advances in Signal Processing , 2006,
Abstract: Publicly available long video traces encoded according to H.264/AVC were analyzed from the fractal and multifractal points of view. It was shown that such video traces, as compressed videos (H.261, H.263, and MPEG-4 Version 2) exhibit inherent long-range dependency, that is, fractal, property. Moreover they have high bit rate variability, particularly at higher compression ratios. Such signals may be better characterized by multifractal (MF) analysis, since this approach describes both local and global features of the process. From multifractal spectra of the frame size video traces it was shown that higher compression ratio produces broader and less regular MF spectra, indicating to higher MF nature and the existence of additive components in video traces. Considering individual frames (I, P, and B) and their MF spectra one can approve additive nature of compressed video and the particular influence of these frames to a whole MF spectrum. Since compressed video occupies a main part of transmission bandwidth, results obtained from MF analysis of compressed video may contribute to more accurate modeling of modern teletraffic. Moreover, by appropriate choice of the method for estimating MF quantities, an inverse MF analysis is possible, that means, from a once derived MF spectrum of observed signal it is possible to recognize and extract parts of the signal which are characterized by particular values of multifractal parameters. Intensive simulations and results obtained confirm the applicability and efficiency of MF analysis of compressed video.
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