Ziv Frame Research Articles

Deep chroma prediction of Wyner–Ziv frames in distributed video coding of wireless capsule endoscopy video

Compression of captured video frames is crucial for saving the power in wireless capsule endoscopy (WCE). A low complexity encoder is desired to limit the power consumption required for compressing the WCE video. Distributed video coding (DVC) technique is best suitable for designing a low complexity encoder. In this technique, frames captured in RGB colour space are converted into YCbCr colour space. Both Y and CbCr representing luma and chroma components of the Wyner–Ziv (WZ) frames are processed and encoded in existing DVC techniques proposed for WCE video compression. In the WCE video, consecutive frames exhibit more similarity in texture and colour properties. The proposed work uses these properties to present a method for processing and encoding only the luma component of a WZ frame. The chroma components of the WZ frame are predicted by an encoder–decoder based deep chroma prediction model at the decoder by matching luma and texture information of the keyframe and WZ frame. The proposed method reduces the computations required for encoding and transmitting of WZ chroma component. The results show that the proposed DVC with a deep chroma prediction model performs better when compared to motion JPEG and existing DVC systems for WCE at the reduced encoder complexity.

A Novel Online Correlation Noise Model Based on Band Coefficients Mean to Achieve Low Computational and Coding-Efficient Distributed Video Codec

Distributed video coding (DVC) is a novel coding paradigm that offers low computational encoding relative to conventional video-coding framework at the expense of high-decoding computational complexity. The challenging part of this video-coding framework is achieving better rate-distortion (RD) compared with conventional codec performance. A suitable and accurate correlation noise model (CNM) is crucial in improving the RD performance by achieving high coding efficiency and making decoding less computationally demanding. Since the correlation is nonstationary and time-variant and can vary from frame to frame, offline CNM estimation is not feasible for practical applications and real-time decoding. An online CNM may be the solution to this problem. In DVC, neither Wyner–Ziv frame (WZF) nor estimated side information (SI) of the corresponding WZF is available at the encoder. Therefore, online estimation of the CNM and its parameters can be quite challenging. The contribution of this research work is a novel online CNM which is computed by taking the mean of each transformed coefficient band and deployed for two different codecs. Our proposed codec, DIVCOM, which stands for “Distributed Video Coding with Online Band Mean Correlation Noise Model”, outperforms the existing baseline codec, DISCOVER (DIS), in both coding efficiency and peak signal-to-noise ratio (PSNR). The DIVCOM codec achieves coding efficiency of up to 8.05 kbps, and PSNR ranges from 0.0245 dB to 0.18 dB. An extended version of DIVCOM incorporating phase-based side information called PDIVCOM achieves coding efficiency up to 10.9 kbps, and PSNR ranges from 0.019 to 0.17 dB compared to DIS.

Side Information Generation Scheme Based on Coefficient Matrix Improvement Model in Transform Domain Distributed Video Coding.

In order to effectively improve the quality of side information in distributed video coding, we propose a side information generation scheme based on a coefficient matrix improvement model. The discrete cosine transform coefficient bands of the Wyner–Ziv frame at the encoder side are divided into entropy coding coefficient bands and distributed video coding coefficient bands, and then the coefficients of entropy coding coefficient bands are sampled, which are divided into sampled coefficients and unsampled coefficients. For sampled coefficients, an adaptive arithmetic encoder is used for lossless compression. For unsampled coefficients and the coefficients of distributed video coding coefficient bands, the low density parity check accumulate encoder is used to calculate the parity bits, which are stored in the buffer and transmitted in small amount upon decoder request. At the decoder side, the optical flow method is used to generate the initial side information, and the initial side information is improved according to the sampled coefficients by using the coefficient matrix improvement model. The experimental results demonstrate that the proposed side information generation scheme based on the coefficient matrix improvement model can effectively improve the quality of side information, and the quality of the generated side information is improved by about 0.2–0.4 dB, thereby improving the overall performance of the distributed video coding system.

Distributed video coding using interval overlapped arithmetic coding

Distributed video coding (DVC) is a flexible and novel video coding mode that is different from traditional video compression methods, which can shift the complex task such as motion estimation from encoder to decoder. Nowadays, most of the DVC architectures adopt channel coding such as low-density parity-check codes. It is found that arithmetic coding can be also extended to compress correlated sources and even has better performance than the channel coding for short to medium block length sources. Therefore, we propose a DVC scheme using interval overlapped arithmetic coding that is distributed arithmetic coding (DAC) without feedback channel, where the Key frames are compressed using traditional video coder while the Wyner–Ziv frames are compressed using DAC. We compare the rate–distortion performance of the proposed scheme with the state-of-the-arts, and the experimental results indicate that the proposed scheme is competitive. The source code for this scheme is available in GitHub.

Decoder side Wyner–Ziv frame estimation using Chebyshev polynomial-based FLANN technique for distributed video coding

In this paper, a Chebyshev polynomial-based functional link artificial neural network (CFLANN) technique for Wyner–Ziv (WZ) frame estimation in a distributed video coding framework is proposed. The estimated WZ frame at the decoder is also referred to as the side information (SI). The proposed scheme (CFLANN-SI) works in two phases, namely, training and testing. The network is trained offline, and to achieve better generalization, the training (input, target) patterns are created across several video sequences constituting varied motion behavior. It estimates the SI frame using adjacent key frames as inputs. The training convergence characteristics of CFLANN-SI is observed to be faster with reduced mean square error as compared to a multi-layer perceptron-based prediction scheme. It is also observed that once the model is trained, it is capable of estimating SI for rest of the incoming WZ frames of the video sequences as well as for the video sequences which are not considered during the learning phase. The proposed scheme is evaluated with respect to different parameters, namely, rate-distortion, peak-signal-to-noise-ratio, the number of parity requests made per estimated frame, decoding time requirement and so on. Comparative analysis shows that the present CFLANN-SI technique generates better SI in resemblance to the competent schemes, in terms of the subjective quality improvement as well as the objective quality gains. Further, to substantiate that the present scheme provides a significant improvement over that of the benchmark techniques, a statistical analysis tool is used with a significance level of 5%.

Distributed Source Coding of Hyperspectral Images Based on Three-Dimensional Wavelet

To reduce the possibility of poor efficiency and weak anti-error capability while encoding and transmitting hyperspectral images, we present a distributed source coding scheme for hyperspectral images based on three-dimensional (3D) set partitioning in hierarchical trees (SPIHT). First, the 3D wavelet transform is performed on the hyperspectral image. Thereafter, the low frequency section is regarded as the Key frame and the high frequency section as the Wyner–Ziv frame to enable independent SPIHT coding through different transmission channels. The Wyner–Ziv encoder uses Turbo channel coding to create high frequency information that reflects the details of the image with better anti-error capacity, while the low frequency information shows the main energy of the image. In this study, we used SPIHT coding to acquire a bit stream with quality scalability. Results show that the proposed scheme is more efficient during coding, while at the same time providing improved anti-error capability and quality scalability of the bit stream.

Multiple descriptions Wyner–Ziv video coding

This paper proposes a multiple descriptions Wyner–Ziv video coding (MDWZVC) architecture, which combines the merits of multiple descriptions coding (MDC) and Wyner–Ziv video coding (WZVC). All of the Wyner–Ziv frames (WZFs) are sub-sampled into four low resolution parallel phases to generate four descriptions, which are encoded and transmitted to the decoder independently. In addition, a successive refined side information (SI) algorithm, which is suitable for the video coding architecture is proposed to exploit both temporal and spatial correlations of the video frames. The simulation results show the SI quality, the peak signal to noise ratio (PSNR) and the rate-distortion (R-D) performance improved with the increasing numbers of received descriptions. By updating the SI quality and reconstruction results of the already decoded descriptions, the R-D performance improved further more. When all of the four descriptions correctly received, the R-D performance improvement of the proposed MDWZVC architecture over DISCOVER codec can be up to 1.8dB, which indicates the effectiveness of the proposed architecture.

Rate-distortion optimised quantisation for direct current coefficients of Wyner–Ziv frame in unidirectional distributed video coding

This study presents a rate-distortion (RD) optimised quantisation algorithm for direct current (DC) coefficients of the Wyner–Ziv (WZ) frames in unidirectional distributed video coding. As the side information (SI) could be viewed as a ‘corrupted’ version of the original WZ frame, the correlation noise (WZ-SI) can be interpreted as a virtual channel with an error pattern. In this study, the distortion caused by virtual channel errors, besides quantisation errors, is analysed emphatically for unidirectional WZ video coding. In their presented quantisation algorithm, a novel RD model is developed to find out the optimal quantisation step size, in which the quantisation distortion and virtual channel error distortion together with the encoding rate are formulated using the quantisation step size without feedback channels. Then the RD optimal step size for DC coefficients can be solved through minimising the RD cost. In simulations, the comparison of RD performance between their proposed algorithm and the quantisation method used in distributed coding for video services (DISCOVER) is presented. Experimental results show that the proposed RD optimised quantisation for DC coefficients can improve the average peak signal-to-noise ratio of WZ frames by 0.4–1.2 dB for quarter common intermediate format (QCIF) sequences and 0.2–0.4 dB for common intermediate format (CIF), at the expense of increasing the encoding complexity slightly.

Feedback-free rate-allocation scheme for transform domain Wyner–Ziv video coding

In most existing Wyner---Ziv video coding schemes, a feedback channel (FC) is expected at the decoder in order to allocate a proper bit rate for each Wyner---Ziv frame. However, FC not only results in additional latency but also increases decoding complexity due to the several feedback-decoding iterations. Moreover, FC may be unavailable in many practical video applications. In this paper, we propose a novel feedback-free rate-allocation scheme for transform domain Wyner---Ziv video coding (TD-WZVC), which predicts the rate for each Wyner---Ziv frame at the encoder without significantly increasing the complexity of the encoder. First, a correlation estimation model is presented to characterize the relationship between the source frame and the reference frame estimated at the encoder in TD-WZVC. Then, an efficient FC-free rate-allocation algorithm is proposed and a linear model is built to avoid both overestimation and underestimation of the real rate and obtain an optimal rate-distortion performance. Experimental results show that the proposed scheme is able to achieve a good encoder rate allocation while still maintaining consistent coding efficiency.

Transform-domain distributed video coding with rate–distortion-based adaptive quantisation

This study presents a transform-domain distributed video coding (DVC) system with a rate–distortion (R–D)-based Adaptive QuanTisation (AQT) scheme. In the proposed system, the transform-domain Wyner–Ziv frame is divided into partitions and is adaptively quantised based on estimated local R–D characteristics for each partition. The R–D estimation is performed based on a correlation model between the original source information and the side information and can be applied at the decoder without adding complexity to the encoder. Coding results and comparisons with existing DVC schemes and with H.264/AVC interframe and intraframe coding are presented to illustrate the performance of the proposed system.

Backward channel aware Wyner–Ziv video coding: A study of complexity, rate, and distortion tradeoff

Wyner–Ziv video coding is a coding method that exploits source statistics at the decoder. Many Wyner–Ziv video coding schemes encode a video sequence into two types of frames, key frames and Wyner–Ziv frames, and rely on the frequent use of INTRA frames as key frames such that the decoder can derive sufficiently accurate side information. While the use of INTRA frame as key frames keeps the encoding complexity low, it also leads to much lower coding efficiency compared to state-of-the-art predictive video coding. In this paper we present a Wyner–Ziv video coding scheme that uses backward channel aware motion estimation to encode the key frames, where motion estimation is performed at the decoder and motion information is sent back to the encoder. Two motion vector selection methods are proposed and we present a model to study the complexity–rate–distortion tradeoff in such coding schemes.