Video Compression Methods Research Articles

Holostream: High-Accuracy, High-Speed 3D Range Video Encoding and Streaming Across Standard Wireless Networks

Holostream is a novel platform which enables high-quality 3D video communication on mobile devices (e.g., iPhones, iPads) using existing standard wireless networks. The major contributions are: (1) a novel high-quality 3D video compression method that drastically reduces both 3D geometry and color texture data sizes in order to transmit them within the bandwidths provided by existing wireless networks; (2) a novel pipeline for 3D video recording, encoding, compression, decompression, visualization and interaction; and (3) a demonstration system which successfully delivered video-rate, photorealistic 3D video content through a standard wireless network to mobile devices. The novel platform improves the quality and expands upon the capabilities of popular applications already utilizing real-time 3D data delivery, such as teleconferencing and telepresence. This technology could also enable emerging applications which may require highresolution, high-accuracy 3D video data delivery, such as remote robotic surgery and telemedicine.

Block Matching Video Compression Based on Sparse Representation and Dictionary Learning

This work presents a video compression method based on sparse representation and dictionary learning algorithms. The proposed scheme achieves superb rate-distortion performance and decent subjective quality, compared to modern standards, especially at low bit-rates. Different from similar works, sparse representation is employed here for both intra-frame and block matching inter-frame motion information. Dividing video frames to reference and current frames, motion vectors and motion compensation residuals of current frames are estimated in regard to reference frames. The sparse codes of reference frames and motion compensation residuals are obtained using learned dictionaries, entropy-coded, and stored or sent to the receiver along with the coded motion field. In the receiver, after decoding the sparse codes and motion vectors, the reference frames and residuals are reconstructed employing the same learned dictionary and the current frames are recovered using the reference frames and motion fields. In the proposed scheme, the Iterative Least Square Dictionary Learning Algorithm (ILS-DLA) and K-SVD dictionary building methods are employed in the DCT domain. The compression rate and quality of the method based on the two dictionary learning algorithms are compared to each other and to H.264/AVC and HEVC modern standards. The results based on PSNR and SSIM criteria show that the proposed approach presents superior performance respect to H.264/AVC and even HEVC for higher bit-rates of QCIF video format, and the K-SVD learning algorithm performs slightly better than the ILS-DLA for the purpose.

Minimum Description Length Sparse Modeling and Region Merging for Lossless Plenoptic Image Compression

This paper proposes a complete lossless compression method for exploiting the redundancy of rectified light-field data. The light-field data consist of an array of rectified subaperture images, called for short views, which are segmented into regions according to an optimized partition of the central view. Each region of a view is predictively encoded using a specifically designed sparse predictor, exploiting the smoothness of each color component in the current view, and the cross similarities with the other color components and already encoded neighbor views. The views are encoded sequentially, using a spiral scanning order, each view being predicted based on several similar neighbor views. The essential challenge for each predictor becomes choosing the most relevant regressors from a large number of possible regressors belonging to the neighbor views. The proposed solution here is to couple sparse predictor design and minimum description length (MDL) principle, where the data description length is measured by an implementable code length, optimized for a class of probability models. This paper introduces a region merging segmentation under the MDL criterion for partitioning the views into regions having their own specific sparse predictors. In experiments, several fast sparse design methods are considered. The proposed scheme is evaluated over a database of plenoptic images, achieving better lossless compression ratios than straightforward usage of standard image and video compression methods for the spiral sequence of views.

Low complexity based ultra-high quality video compression method for multimedia-centric internet of things (IoT) services

Internet of things (IoT) enables a number of embedded systems to interact for the purpose of various IoT applications such as home security, medical, smart surveillance, and etc. It is expected that the need of multimedia computing for ultra-high quality video delivery has further increased the importance of fast and complexity-awareness video compression algorithm under low-complexity and low-power IoT systems. High efficiency video coding (HEVC) is the state-of-the-art video coding technology that can provide powerful video compression performance under limited bandwidth conditions for transmission or storage. Although HEVC adopted newly advanced video coding tools to achieve a bitrate reduction of 50% with similar video quality compared to the previous method, H.264/AVC, these cause heavy computational encoding complexity resulting from inter prediction process of HEVC encoder. In this paper, we propose a complexity scalable SKIP/MERGE encoding algorithm to design a low complexity inter prediction. Experimental results show that the proposed method is much faster than those of HEVC test model (47.42%) and previous method (13.95%) in terms of total encoding time, on average.

Evaluation of Impairment Caused by MPEG Video Frame Loss

This article presents a study on the impact of video frame losses on the quality perceived by users. Video compression standards, such as MPEG, use a sequence of frames called Group of Pictures (GOP), which is a video compression method which a frame is expressed in terms of one or more neighboring frames. This dependence between frames impacts directly in the quality because a loss of a reference frame prevents the decoding of other frames in GOP, thereby reducing the user-perceived quality. The assessment of quality in this article is estimated by Peak Signal Noise Ratio (PSNR), which compares the original and the received images. Computer simulations were used to show that the degradation on the quality may vary for different patterns of GOPs and type of lost frames.

New context of compression problem and approach to solution: a survey of the literature

The new generation multimedia applications such as ultra-high definition TV, 3D video and cloud storage keeps the compression research relevant even post to the advent of the state-of-art standard HEVC (High Efficiency Video Coding) codec. The continued studies on human visual system suggest that a perceptually acceptable reconstruction with reduced bandwidth requirements may be more acceptable and commercially viable solution rather than a bit accurate reconstruction for a variety of video and graphics applications. One way to achieve compression beyond that achieved by the advanced codec like HEVC is to sample the input data at a lower rate than the Nyquist rate, exploit the sparsity and perceptual redundancy in the content using advanced signal processing and computer vision tools and represents it using a spatio-temporal model. This paper contains an exhaustive review of the new context of video compression methods along with their limitations and open issues.

An evaluation of power transfer functions for HDR video compression

High dynamic range (HDR) imaging enables the full range of light in a scene to be captured, transmitted and displayed. However, uncompressed 32-bit HDR is four times larger than traditional low dynamic range (LDR) imagery. If HDR is to fulfil its potential for use in live broadcasts and interactive remote gaming, fast, efficient compression is necessary for HDR video to be manageable on existing communications infrastructure. A number of methods have been put forward for HDR video compression. However, these can be relatively complex and frequently require the use of multiple video streams. In this paper, we propose the use of a straightforward Power Transfer Function (PTF) as a practical, computationally fast, HDR video compression solution. The use of PTF is presented and evaluated against four other HDR video compression methods. An objective evaluation shows that PTF exhibits improved quality at a range of bit-rates and, due to its straightforward nature, is highly suited for real-time HDR video applications.

An Efficient Video Compression Technique Using Watershed Algorithm and JPEG-LS Encoding

In the previous video compression method, the videos were segmented by using the novel motion estimation algorithm with aid of watershed method. But, the compression ratio (CR) of compression with novel motion estimation algorithm was not giving an adequate result. Moreover this methods performance is needed to be improved in the encoding and decoding processes. Because most of the video compression methods have utilized encoding techniques like JPEG, Run Length, Huffman coding and LSK encoding. The improvement of the encoding techniques in the compression process will improve the compression result. Hence, to overcome these drawbacks, we intended to propose a new video compression method with renowned encoding technique. In this proposed video compression method, the input video frames motion vectors are estimated by applying watershed and ARS-ST (Adaptive Rood Search with Spatio-Temporal) algorithms. After that, the vector blocks which have high difference value are encoded by using the JPEG-LS encoder. JPEG-LS have excellent coding and computational efficiency, and it outperforms JPEG2000 and many other image compression methods. This algorithm is of relatively low complexity, low storage requirement and its compression capability is efficient enough. To get the compressed video, the encoded blocks are subsequently decoded by JPEG-LS. The implementation result shows the effectiveness of proposed method, in compressing more number of videos. The performance of our proposed video compression method is evaluated by comparing the result of proposed method with the existing video compression techniques. The comparison result shows that our proposed method acquires high-quality compression ratio and PSNR for the number of testing videos than the existing techniques.

Fast Quadtree Based Normalized Cross Correlation Method for Fractal Video Compression using FFT

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

Ultrasound Video Streaming using HEVC-XLD in WiMAX Networks

Medical video communication system has been adopted widely in standard clinical practise to provide an adequate quality video diagnostic. In the existing m-health application, significant advance methods has been produced to emerge the high efficiency video compression methods with a promising wireless network for emergency situation in daily clinical practice. To transmit the medical ultrasound video effectively from user side to expert side, this proposed work utilize the upcoming standard technique High efficiency video coding (HEVC) for video compression. HEVC provides equal perceptual video quality by 50% bit-rate reduction range with high-resolution and low-delay video transmission. The cross layer framework over the WiMAX network is adapted to improve the throughput of the network considerably and the quality of service is optimized in the network environments. The experimental evaluations of the proposed scheme indicate that it produce a higher PSNR rate per frame and the best high resolution ultrasound video quality.

DWT Based-Video Compression Using (4SS) Matching Algorithm

Currently, multimedia technology is widely used. Using the video encoding compression technology can save storage space, and also can improve the transmission efficiency of network communications. In video compression methods, the first frame of video is independently compressed as a still image, this is called intra coded frame. The remaining successive frames are compressed by estimating the disparity between two adjacent frames, which is called inter coded frame. In this paper, Discrete Wavelet Transform (DWT) is used powerful tool in video compression. Our coder achieves a good trade-off between compression ratio and quality of the reconstructed video.
 The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The disparity between each two frames was estimated by Four Step Search (4SS) Algorithm. The result of the Motion Vector (MV) was encoded into a bit stream by Huffman encoding while the remaining part is compressed like the compression was used in intra frame. Experimental results showed good results in terms of Peak Signal-to-Noise Ratio (PSNR), Compression Ratio (CR), and processing time.

SURF 특징과 블록 모양을 이용한 동영상 압축 방법

Today, computer network infrastructure is commonplace and internet user increase. Transmission bandwidth for network traffic is increasing. The data amount of 2014 and 2015 year measured 47 and 62 exabyte, it shows a tremendous increase. Video traffic occupy 60 percent among internet traffic. Enormous growth of Internet traffic than the network infrastructure is not enough to support them, so mobile network occur side-effects such as fall of voice communication. In this paper, we proposed the video compression method using SURF feature and block shaping in order to avoid potential damage. Our proposed method can provide enough performance than previous method.

Human centered perceptual adaptation for video coding

Traditional visual saliency based video compression methods try to encode the image with higher quality in the region of saliency. However, the saliency feature changes according to persons, viewpoints, and distances. In this paper, we propose to apply a technique of human centered perceptual computation to improve video coding in the region of human centered perception. To detect the region of interest (ROI) of human body, upper body, frontal face, and profile face, we construct Harr and histogram of oriented gradients features based combo of detectors to analyze a video in the first frame (intra-frame). From the second frame (inter-frame) onward, the optical flow image is computed in the ROI area of the first frame. The optical flow in human centered ROI is then used for macroblock (MB) quantization adjustment in H.264/AVC. For each MB, the quantization parameter (QP) is optimized with density value of optical flow image. The QP optimization process is based on a MB mapping model, which can be calculated by an inverse of the inverse tangent function. The Lagrange multiplier in the rate distortion optimization is also adapted so that the MB distortion at human centered region is minimized. We apply our technique to the H.264 video encoder to improve coding visual quality. By evaluating our scheme with the H.264 reference software, our results show that the proposed algorithm can improve the visual quality of ROI by about 1.01 dB while preserving coding efficiency.

Spatio-Temporal Wavelet Based Video Compression: a Simulink Implementation for Acceleration

In this paper, we presented a Wavelet based video compression method. The wavelet transform is performed by lifting scheme methodology which allows temporal and special scalability as well as lossless reconstruction. The spatial decorrelation was elaborated with the standard JPEG2000. We exploited the inter-frames correlation thanks to a temporal wavelet transformation. A Simulink based implementation is then experimented in order to accelerate the process thanks to a co-simulation step

Different Approach of VIDEO Compression Technique: A Study

The main objective of video compression is to achieve video compression with less possible losses to reduce the transmission bandwidth and storage memory. This paper discusses different approach of video compression for better transmission of video frames for multimedia application. Video compression methods such as frame difference approach, PCA based method, accordion function, fuzzy concept, and EZW and FSBM were analyzed in this paper. Those methods were compared for performance, speed and accuracy and which method produces better visual quality.

Fast Video Compression Method based on Wavelet Transform and Simple Efficient Search Algorithm

In this paper, a fast video compression method has been proposed. In proposed method, Firstly, frames were transformed using Discrete Wavelet Transform (DWT) in order to reduce computation time. The disparity between each two adjacent frames was estimated by Simple and Efficient Search (SES) algorithm. The result of the Motion Vector (MV) was encoded into a bit stream by Huffman encoding while the remaining part is compressed like the compression that is used in still image. The proposed method produced good results in terms of Peak Signal-to-Noise Ratio (PSNR), CR, and computation time.

Object-based stereo video compression using fractals and shape-adaptive DCT

Based on the classical fractal video compression method, an improved object-based stereo video compression scheme with Shape-Adaptive DCT is proposed in this paper. Firstly, we use more effective macroblock partition scheme instead of classical quadtree partition scheme; thus reducing the block searching strategy. The stereo fractal video coding is proposed which matches the macroblock with two reference frames in left and right view results in increasing compression ratio and reducing bit rate when transmitting compressed stereo data. The stereo codec combines the Motion Compensation Prediction (MCP) and Disparity Compensation Prediction (DCP). Fractal coding is adopted and each object is encoded independently by a prior video segmentation alpha plane, which is defined exactly as in MPEG-4. The testing results with the nature monocular and stereo video sequences provide promising performances at low bit rate coding. We believe it will be a powerful and efficient technique for the object-based monocular and stereo video sequences coding.

H.264 기반 HD급 VOD 콘텐츠관리시스템 상호운용성 개선

Abstract Recently, although the requirement of quality of VOD content has been transferred upto the class of HD, conventional management systems characterized by OS dependency are truly limited in quality of video image, stability, and compatibility of network environments. In addition most of the content management systems realize very limited capabilities for the real affairs of content management and distribution services in such an OS dependent environment. In this paper, we propose a new scheme of HD-Class VOD Content Management System to solve these problems. We design and implement the proposed system based on open sources by using H.264 video compression method. The proposed system offers high quality content management method based on opened systems and independent on-line distribution method so that it can be realized as an integrated management scheme for VOD contents. Moreover, our system solves the problems of occasional cutting-down video, small screen, and poor image quality that exist in the conventional wmv-type CMS. According to the result of performance evaluation, our system maintains sufficient performance and tolerence for the case of large scale HD content operations or fabrications. We expect that the proposed integrated DB scheme will especially be effective when the content management applications are changed from Internet Web environments to mobile terminal environments.

An adaptive system for compressed video deblocking

Many state of the art methods for video compression rely on the Discrete Cosine Transform (DCT) and the quantization of its coefficients. Here we present a video deblocking system which is based on the properties of the DCT. Hence it is suitable for MPEG-2 compressed videos, since the MPEG-2 standard belongs to this class of compression formats. The system carries out an online analysis of the video in order to adapt its operation to the characteristics of the incoming video frames. Experiments with benchmark real videos are shown, which demonstrate the performance of our proposal both in quantitative and qualitative terms.

Fractal Video Compression using Block Matching Motion Estimation - A Study

The large usage of multimedia applications on internet and mobiles has increased the demand of compressed data, as to reduce the bandwidth requirement and transmission time. So block based method for video compression is getting more importance due to its effectiveness and easy implementation. Fractal video compression follows the property of self-similarity. The weighted finite automata exploits the property of selfsimilarity in a single image or sequence of images. In block matching motion estimation various algorithm has been proposed having different search pattern and strategies. The paper presents the review on different methods for fractal video compression.