A Lossless Embedded Compression Using Significant Bit Truncation for HD Video Coding

Kim, Jae-Moon; Kyung, Chong-Min

doi:10.1109/tcsvt.2010.2045923

Cited by 81 publications

(5 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A lot of work has been done on software and hardware of mobile devices to extend the battery lifetime. For example, low complexity encoding strategies [5–7], low power embedded video coding algorithm [8], adaptive power control strategies [9–11], and joint encoding and hardware adaptive method [12] are proposed as the possible solutions. However, performance enhancement resulting from these researches cannot meet the increasing requirements of energy saving by users.…”

Section: Related Workmentioning

confidence: 99%

QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices

Zhang

Chen

et al. 2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Over the last couple of years, video service distribution among smart phones and other mobile video devices is becoming increasingly popular in sensor networks. However, the huge energy consumption caused by video encoding and transmitting and the slowly evolving battery technologies become the major bottlenecks that hinder the development of video streaming services. Hence energy efficient video coding and transmitting solutions are required to be investigated. Yet, energy consumption reduction of mobile video devices will be accompanied with Quality of Experience (QoE) degradation of video applications. Such diverse tendency makes it difficult to encode and transmit video streams with less energy as well as better QoE. This paper analyzes the major energy consuming factors in mobile video devices. A specific energy consumption model concerning encoding bitrates and transmitting power level is built. Further, a noninvasive QoE perceptive model is adopted so that the energy efficiency problem becomes a cross-layer optimization problem. Chaos particle swarm optimization is used to solve this cross-layer optimization problem with fast convergence. By this method, energy consumption of mobile video device is minimized with acceptable QoE for video users. At last, Pareto front of energy and QoE is analyzed to certify the performance of our method.

show abstract

Section: Related Workmentioning

confidence: 99%

QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices

Zhang

Chen

et al. 2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…The fixed rounding scheme is based on the smallest compression unit, i.e. one pixel [7]. Compared with it, the methods based on 4x4 blocks [8,9] increase the memory access bandwidth remarkably (about 40%) when the align/  burst parameters are low.…”

Section: ) the Basic Access Unit Size Is Determined By Compression Unmentioning

confidence: 99%

“…proposed the method using Huffman based variable length coding table to achieve lossless compression. [7] This kind of methods has been utilized by some hardware designers. [8], [9] However, this vlc table based method could not obey the principle of random access, which could increase complex computation and delay.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Granularity selection in Reference Picture Memory Compression

Ma¹,

Kang²

2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

View full text Add to dashboard Cite

Memory size occupation and memory access bandwidth are capital issues for high resolution video codec design because of the large scale of data, and the high power consumption especially for wireless terminals. An adaptive and random access-obeyed reference pictures memory compression (RPMC) scheme based on as small granularity as 2x2 blocks for 2-bit truncation is proposed in this paper to solve the problems. The impact of granularity in RPMC to memory access bandwidth during motion estimation and/or motion compensation is analyzed firstly. Then an adaptive RPMC scheme based on 2x2 block size is proposed, based on min-max scalar quantization (MMSQ). Finally, the results based on HM are provided which show that compared with the common used 4x4 block-based methods, little performance loss is introduced. At the same time, based on the adaptively merge scheme, the average memory access bandwidth is saved than the 4x4 block based method by up to 17%.

show abstract

“…There are many video compression algorithms proposed in the literature, including those targeting mobile devices, e.g., smart phones and tablets [19,20]. Current compression techniques aim at minimizing information redundancy in video sequences [21,22]. An example of such techniques is motion compensated (MC) predictive coding.…”

Section: Introductionmentioning

confidence: 99%

Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics

et al. 2020

View full text Add to dashboard Cite

The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, recognition and understanding and efficient processing of large amounts of video data. This research proposes a novel unified approach to lossy and lossless video frame compression, which is beneficial for the autonomous processing and enhanced representation of high-resolution video data in various domains. The proposed fast block matching motion estimation technique, namely mean predictive block matching, is based on the principle that general motion in any video frame is usually coherent. This coherent nature of the video frames dictates a high probability of a macroblock having the same direction of motion as the macroblocks surrounding it. The technique employs the partial distortion elimination algorithm to condense the exploration time, where partial summation of the matching distortion between the current macroblock and its contender ones will be used, when the matching distortion surpasses the current lowest error. Experimental results demonstrate the superiority of the proposed approach over state-of-the-art techniques, including the four step search, three step search, diamond search, and new three step search.

show abstract

A Lossless Embedded Compression Using Significant Bit Truncation for HD Video Coding

Cited by 81 publications

References 33 publications

QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices

QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices

Adaptive Granularity selection in Reference Picture Memory Compression

Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics

Contact Info

Product

Resources

About