Residual Wavelet-Domain DVC Using an Optimized TCQ

2011 ◽  
Vol 58-60 ◽  
pp. 2079-2084
Author(s):  
An Hong Wang ◽  
Yi Zheng ◽  
Zhi Hong Li ◽  
Yu Yang Wang

Nowadays, the rate-distortion performance of distributed video coding (DVC) is not satisfied despite its distinct contribution to low-complexity encoding. This paper presents a new residual DVC using an optimized trellis coded quantization (TCQ) to improve the performance of the current schemes. H.264/AVC intra-frame coding is firstly used to obtain the referenced frame, and then the residual between Wyner-Ziv frame and the referenced frame is Wyner-Ziv encoded with a proposed optimized TCQ which consists of the improved quadtree and the improved TCQ, both considering the characters of wavelet coefficients in different sub-bands. Experimental results show that the proposed scheme outperforms the referenced in rate-distortion performance, and the goal of low-complexity encoding is achieved.

Author(s):  
Huynh Van Luong ◽  
Søren Forchhammer ◽  
Jürgen Slowack ◽  
Jan De Cock ◽  
Rik Van de Walle

Distributed video coding (DVC) is a coding paradigm that entails low complexity encoding by exploiting the source statistics at the decoder. To improve the DVC coding efficiency, this paper presents a novel adaptive technique for mode decision to control and take advantage of skip mode and intra mode in DVC initially proposed by Luong et al. in 2013. The adaptive mode decision (AMD) is not only based on quality of key frames but also the rate of Wyner–Ziv (WZ) frames. To improve noise distribution estimation for a more accurate mode decision, a residual motion compensation is proposed to estimate a current noise residue based on a previously decoded frame. The experimental results, integrating AMD in two efficient DVC codecs, show that the proposed AMD DVC significantly improves the rate distortion performance without increasing the encoding complexity. For a GOP size of 2 on the set of six test sequences, the average (Bjøntegaard) bitrate saving of the proposed codec is 35.5% on WZ frames compared with the DISCOVER codec. This saving is mainly achieved by AMD.


2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Bingyu Ji ◽  
Ran Li ◽  
Changan Wu

Compressive-Sensing Video Coding (CSVC) is a new video coding framework based on compressive-sensing (CS) theory. This paper presents the evaluations on rate-distortion performance and rate-energy-distortion performance of CSVC by comparing it with the popular hybrid video coding standard H.264 and distributed video coding (DVC) system DISCOVER. Experimental results show that CSVC achieves a poor rate-distortion performance when compared with H.264 and DISCOVER, but its rate-energy-distortion performance has a distinct advantage; moreover, its energy consumption of coding is approximately invariant regardless of reconstruction quality. It can be concluded that, with a limited energy budget, CSVC outperforms H.264 and DISCOVER, but its rate-distortion performance still needs improvement.


2021 ◽  
Vol 30 ◽  
pp. 2378-2393
Author(s):  
Meng Wang ◽  
Shiqi Wang ◽  
Junru Li ◽  
Li Zhang ◽  
Yue Wang ◽  
...  

2013 ◽  
Vol 281 ◽  
pp. 47-50
Author(s):  
Zhi Hong Chen

In this paper we propose a new steganographic method, which based on wet paper codes and wavelet transformation. The method is designed to embed secret messages in images' wavelet coefficients and depends on images' texture characters in local neighborhood. The receivers can extract secret bits from carrier images only by some matrix multiplications without knowing the formulas written by senders, which further improves steganographic security and minimizes the impact of embedding changes. The experimental results show that our proposed method has good robust and visual concealment performance and proves out it's a practical steganographic algorithm.


Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 130 ◽  
Author(s):  
Dinh Trieu Duong ◽  
Huy Phi Cong ◽  
Xiem Hoang Van

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.


2017 ◽  
Vol 11 (2) ◽  
pp. 126-134 ◽  
Author(s):  
Pudi Raj Bhagath ◽  
Kallol Mallick ◽  
Jayanta Mukherjee ◽  
Sudipta Mukopadhayay

2014 ◽  
Vol 599-601 ◽  
pp. 1360-1363
Author(s):  
Xiang Yan Liang ◽  
Zhen Hua Tang ◽  
Ya Dan Luo ◽  
Tuan Fa Qin

In order to improve the accuracy of correlated noise (CN) model for distributed video coding (DVC), this paper proposes a novel distribution parameter fitting algorithm based on the minimum Euclidean distance. The presented method can obtain the final fitted distribution parameter by using the minimum Euclidean distance to compare the Laplace probability density function (PDF) with the PDF computed utilizing the actual residual frame data. Experiment results show that the proposed distribution parameter fitting algorithm can improve the rate-distortion (R-D) performance of DVC significantly.


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