Quality Of Video Frames Research Articles

Network-status aware quality adaptation algorithm for improving real-time video streaming over the internet

Video streaming over Internet has been gaining momentum and several quality adaptation schemes have been reported to improve quality of the streamed videos. Most of these schemes focus on adjusting the video encoding rate to match certain network conditions. This paper presents a new quality adaptation algorithm for real-time video streaming over Internet. The proposed algorithm is based upon simultaneous adaptation of multiple key parameters such as video frame rate, resolution, and frame quality to achieve the best possible video quality and minimize possibility of service interruption in lossy networks. Furthermore, the current network status and motion of the streamed video sequence have also been taken into account throughout the adaptation process. A video conferencing test-bed which incorporates the Adobe Flash Real-Time Media Flow Protocol (RTMFP) is built and utilized to investigate the effect of various combinations of the video parameters under study on the quality of sample video clips streamed at slow, medium and fast motions. A quality-adaptation algorithm based on experimental investigations is then developed and its performance is assessed using both subjective and objective evaluations. The obtained results and observations demonstrate superior performance of the developed adaptation algorithm as compared to equivalent algorithms with fixed video quality settings at similar test conditions.

An Efficient and Robust High Efficiency Video Coding Framework to Enhance Perceptual Quality of Real-Time Video Frames

Different level of compression on real-time video streaming has successfully reduced the storage space complexities and bandwidth constraints in the recent times. This paper aims to design and develop a novel concept towards the enhancement of perceptual quality of a real-time video frames. The proposed model has been experimented considering multi-level compression operation using H.265 where .avi moving frames standards play a crucial role. The study also applies a novel concept of High-efficiency video coding (HEVC) for adaptive live video streaming over a mobile network. The proposed study aims to formulate a multi-level optimization for HEVC to enhance the performance of both encoding and decoding mechanisms at the client as well as server side to ensure higher compression rate. The experimental outcomes also show that the proposed protocol achieves better performance ratio and overall; throughput in comparison with conventional H.263, H.264 by enhancing the perceptual quality of .avi format real-time video frames.

Multiresolution Video Watermarking Algorithm Exploiting the Block-Based Motion Estimation

This paper presents a novel technique for embedding a digital watermark into video frames based on motion vectors and discrete wavelet transform (DWT). In the proposed scheme, the binary image watermark is divided into blocks and each watermark block is embedded several times in each selected video frame at different locations. The block-based motion estimation algorithm is used to select the video frame blocks having the greatest motion vectors magnitude. The DWT is applied to the selected frame blocks, and then, the watermark block is hidden into these blocks by modifying the coefficients of the Horizontal sub-bands (HL). Adding the watermark at different locations in the same video frame makes the scheme more robust against different types of attacks. The method was tested on different types of videos. The average peak signal to noise ratio (PSNR) and the normalized correlation (NC) are used to measure the performance of the proposed method. Experimental results show that the proposed algorithm does not affect the visual quality of video frames and the scheme is robust against a variety of attacks.

Discrete Cosine Transformer Based Visual Secret Sharing With Chaos Visual Cryptography

With the increasing threats on multimedia information sharing, degradation of security is one of the most important concerns. Visual Cryptography is an emerging field for improving the security level by encoding the secret video using encryption scheme and performs computational free decoding process. The secret sharing through visual cryptographic techniques for multiple stack users is not sufficient in providing high percentage result on video sharing domain. Video sharing did not develop source key properties for individual frames and as a result the quality estimation strategy on video frame was not achieved. Moreover, the target rate constraint for video quality under the encryption-decryption was not achieved. This encryption-decryption target key rate declines on arranging multiple sequences of frames from multiple stack users. To improve the quality of visual secret video sharing scheme, a Discrete Cosine Transform Chaos Cryptographic (DCTCC) mechanism is proposed in this paper. The main objective of DCTCC is to enhance the security level of different level video frame using the encryption key properties. Initially, sender takes the video of differing frame length and compresses the video on image using the Discrete Cosine Transformer. The Discrete Cosine Transformer based visual secret sharing of video in the image takes the luminance values and provides high lossless compression. Second, the embedded video frame is encrypted to perform the secret sharing (i.e., visual cryptographic) using the chaos method. The Chaos method uses the enhanced RSA key properties to improve the video quality estimation strategy. Chaos method in DCTCC works effectively with non-linear dynamic set of video frames from users and also with the discrete time dynamical video cryptographic system. On the decryption side, the chaos method is applied in the reverse procedural order to fetch the video quality of video frames from original image. Experiment is conducted on factors such as mean square error rate, and secret video sharing efficacy level and encryption time.

Adaptive interface selection over cloud-based split-layer video streaming via multi-wireless networks

As mobile devices such as tablet PCs and smartphones proliferate, the online video consumption over a wireless network has been accelerated. From this phenomenon, there are several challenges to provide the video streaming service more efficiently and stably in the heterogeneous mobile environment. In order to guarantee the QoS of real-time HD video services, the steady and reliable wireless mesh is necessary. Furthermore, the video service providers have to maintain the QoS by provisioning streaming servers to respond the clients' request of different video resolution. In this paper, we propose a reliable cloud-based video delivery scheme with the split-layer SVC encoding and real-time adaptive multi-interface selection over LTE and WiFi links. A split-layer video streaming can effectively scale to manage the required channels on each layer of various client connections. Moreover, split-layer SVC model brings streaming service providers a remarkable opportunity to stream video over multiple interfaces (e.g. WiFi, LTE, etc.) with a separate controlling based on their network status. Through the adaptive interface selection, the proposed system aims to ensure the maximizing video quality which the bandwidth of LTE/WiFi accommodates. In addition, the system offers cost-effective streaming to mobile clients by saving the LTE data consumption. In our system, an adaptive interface selection is developed with two different algorithms, such as INSTANT and EWMA methods. We implemented a prototype of mobile client based on iOS particularly by using iPhone5S. Moreover, we also employ the split-layer SVC encodes in streaming server-side as the add-on module to SVC reference encoding tool in a virtualized environment of KVM hypervisor. We evaluated the proposed system in an emulated and a real-world heterogeneous wireless network environments. The results show that the proposed system not only achieves to guarantee the highest quality of video frames via WiFi and LTE simultaneous connection, but also efficiently saves LTE bandwidth consumption for cost-effectiveness to client-side. Our proposed method provides the highest video quality without deadline misses, while it consumes 50.6% LTE bandwidth of 'LTE-only' method and 72.8% of the conventional (non-split) SVC streaming over a real-world mobile environment. We model an adaptive multi-interface selection video streaming system.A prototype is developed on iOS (iPhone5s) device via LTE and WiFi network.We evaluate the system in an emulated environment and diverse real-world network.Maximizing video quality is guaranteed which the aggregate bandwidth can accommodate.System shows the cost-effectiveness by lower LTE bandwidth consumption.

Adaptive stereo medical image watermarking using non-corresponding blocks.

Today with the advent of technology in different medical imaging fields, the use of stereoscopic images has increased. Furthermore, with the rapid growth in telemedicine for remote diagnosis, treatment, and surgery, there is a need for watermarking. This is for copyright protection and tracking of digital media. Also, the efficient use of bandwidth for transmission of such data is another concern. In this paper an adaptive watermarking scheme is proposed that considers human visual system in depth perception. Our proposed scheme modifies maximum singular values of wavelet coefficients of stereo pair for embedding watermark bits. Experimental results show high 3D visual quality of watermarked video frames. Moreover, comparison with a compatible state of the art method shows that the proposed method is highly robust against attacks such as AWGN, salt and pepper noise, and JPEG compression.

Distributed Video Compressive Sensing Reconstruction by Adaptive PCA Sparse Basis and Nonlocal Similarity

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

On the Suitability of Using ANT Colony Optimization for Routing Multimedia Content over Wireless Sensor Networks

This paper studies the suitability of using a meta-heuristic ant colony technique in routing multimedia content over wireless sensor networks. The presented technique is both energy and QoS-aware. Ant colony algorithm is used to find the optimal routing path. Optimality is in the sense of minimizing energy consumption and increasing link quality and reliability. The proposed approach results in minimizing energy consumption and prolonging the lifetime of the network. Moreover, the optimal path has a high link quality and reliability which enhances video frame quality and ensures high probability of successful delivery of video frames. The importance given to energy consumption, link quality, and link reliability metrics can be varied depending on the multimedia application requirements.

No-Reference Quality Assessment for Networked Video via Primary Analysis of Bit Stream

A no-reference (NR) quality measure for networked video is introduced using information extracted from the compressed bit stream without resorting to complete video decoding. This NR video quality assessment measure accounts for three key factors which affect the overall perceived picture quality of networked video, namely, picture distortion caused by quantization, quality degradation due to packet loss and error propagation, and temporal effects of the human visual system. First, the picture quality in the spatial domain is measured, for each frame, relative to quantization under an error-free transmission condition. Second, picture quality is evaluated with respect to packet loss and the subsequent error propagation. The video frame quality in the spatial domain is, therefore, jointly determined by coding distortion and packet loss. Third, a pooling scheme is devised as the last step of the proposed quality measure to capture the perceived quality degradation in the temporal domain. The results obtained by performance evaluations using MPEG-4 coded video streams have demonstrated the effectiveness of the proposed NR video quality metric.

Video streaming over the internet with optimal bandwidth resource allocation

In this paper, an adaptive framework for video streaming over the Internet is presented. The framework is a joint design of packet scheduling and rate control with optimal bandwidth resource allocation. The transmission rate is dynamically adjusted to obtain maximal utilization of the client buffer and minimal allocation of the bandwidth. Under the constraint of the transmission rate, a prioritized packet scheduling is designed to provide a better visual quality of video frames. The packet scheduling is a refined bandwidth allocation which takes into account of varying importance of the different packets in a compressed video stream. Moreover, the proposed approach is scalable with increasing multimedia flows in the distributed Internet environment. Comparisons are made with the most current streaming approaches to evaluate the performance of the framework using the H.264 video codec. The extensive simulation results show that the average Peak Signal to Noise Ratio (PSNR) increases in our proposed approach. It provides a better quality of the decoded frames, and the quality of the decoded frames changes more smoothly. The achieved video quality among different users also has a lower fluctuation, which indicates a fair sharing of network resources.

Model-based analysis of flow-mediated dilation and intima-media thickness.

We present an end-to-end system for the automatic measurement of flow-mediated dilation (FMD) and intima-media thickness (IMT) for the assessment of the arterial function. The video sequences are acquired from a B-mode echographic scanner. A spline model (deformable template) is fitted to the data to detect the artery boundaries and track them all along the video sequence. The a priori knowledge about the image features and its content is exploited. Preprocessing is performed to improve both the visual quality of video frames for visual inspection and the performance of the segmentation algorithm without affecting the accuracy of the measurements. The system allows real-time processing as well as a high level of interactivity with the user. This is obtained by a graphical user interface (GUI) enabling the cardiologist to supervise the whole process and to eventually reset the contour extraction at any point in time. The system was validated and the accuracy, reproducibility, and repeatability of the measurements were assessed with extensive in vivo experiments. Jointly with the user friendliness, low cost, and robustness, this makes the system suitable for both research and daily clinical use.