Video compression based on hybrid transform and quantization with Huffman coding for video codec

Bernatin, T.; Sundari, G.

doi:10.1109/iccicct.2014.6993004

Cited by 10 publications

(5 citation statements)

References 3 publications

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“…Some limitations are 1) the developed LECSA is suitable only for WSN with multiple nodes used in Environmental Monitoring applications. 2) Nodes with camera as sensor, sends and receives video using compression [27] (T. Bernatin and G.Sundari 2015). For those types this protocol is tough to be implemented, since data aggregation leads to loss in actual video.…”

Section: -Conclusionmentioning

confidence: 99%

Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications

Rathna¹,

Gladence²,

Cynthia³

et al. 2021

JIST

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Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electromechanical sensors through wireless data communication. Nowadays the WSN has become ubiquitous. WSN is used in combination with Internet of Things and in many Big Data applications, it is used in the lower layer for data collection. It is deployed in combination with several high end networks. All the higher layer networks and application layer services depend on the low level WSN in the deployment site. So to achieve energy efficiency in the overall network some simplification strategies have to be carried out not only in the Medium Access Control (MAC) layer but also in the network and transport layers. An energy efficient algorithm for scheduling and clustering is proposed and described in detail. The proposed methodology clusters the nodes using a traditional yet simplified approach of hierarchically sorting the sensor nodes. Few important works on cross layer protocols for WSNs are reviewed and an attempt to modify their pattern has also been presented in this paper with results. Comparison with few prominent protocols in this domain has also been made. As a result of the comparison one would get a basic idea of using which type of scheduling algorithm for which type of monitoring applications.

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Section: -Conclusionmentioning

confidence: 99%

Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications

Rathna¹,

Gladence²,

Cynthia³

et al. 2021

JIST

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“…Such a quantization parameter allocation method lacks adaptability and will inevitably lead to a waste of bitrate and a reduction in rate-distortion performance. Since quantization will bring distortion to the compressed video data; it is particularly important to develop efficient and low-complexity quantizers and study efficient quantization algorithms [22,23]. During the HEVC standardization process, many improvements to the quantization method were proposed.…”

Section: Introductionmentioning

confidence: 99%

Research on Quantization Parameter Decision Scheme for High Efficiency Video Coding

Jin,

Chai

2023

Applied Sciences

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High-Efficiency Video Coding (HEVC) is one of the most widely studied coding standards. It still uses the block-based hybrid coding framework of Advanced Video Coding (AVC), and compared to AVC, it can double the compression ratio while maintaining the same quality of reconstructed video. The quantization module is an important module in video coding. In the process of quantization, quantization parameter is an important factor in determining the bitrate in video coding, especially in the case of limited channel bandwidth. It is particularly important to select a reasonable quantization parameter to make the bitrate as close as possible to the target bitrate. Aiming at the problem of unreasonable selection of quantization parameters in codecs, this paper proposes using a differential evolution algorithm to assign quantization parameter values to the coding tree unit (CTU) in each frame of 360-degree panoramic video based on HEVC so as to strike a balance between bitrate and distortion. Firstly, the number of CTU rows in a 360-degree panoramic video frame is considered as the dimension of the optimization problem. Then, a trial vector is obtained by randomly selecting the vectors in the population for mutation and crossover. In the mutation step, the algorithm generates a new parameter vector by adding the weighted difference between two population vectors to a third vector. And the elements in the new parameter vector are selected according to the crossover rate. Finally, the trial vector is regarded as the quantization parameter of each CTU in the CTU row to encode, and the vector with the least rate distortion is selected. The algorithm will produce the optimal quantization parameter combination for the current video. The experimental results show that compared to the benchmark algorithm of HEVC reference software HM-16.20, the proposed algorithm can provide a bit saving of 1.86%, while the peak signal-to-noise ratio (PSNR) can be improved by 0.07 dB.

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“…So, the image starts with left corner pixel and ends with right corner pixel. The video signals are converted with image and calculating the speed is called a frame rate [3]. Digital video compression techniques play a vital role that enables efficient transmission and storage of multimedia content in bandwidth and storage space limited environment [4].…”

Section: Introductionmentioning

confidence: 99%

H. 264 encoder using Gstreamer

Sundari

Bernatin

Somani

2015

2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]

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To satisfy the requirements of high quality and low bit stream video for real time applications, video compression techniques are used. The most powerful video formats for the video codec are Video Coding Experts Group (VCEG) and ISO/IEC JTC1 Moving Picture Experts Group (MPEG). It is frequently used in internet streaming sources i.e. from media servers to end users. This paper focuses on streaming Video using Gstreamer. The video is captured using a web camera interfaced to PC, encoded using x264 and the video is streamed through Gstreamer and results a very good compression ratio.

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Video compression based on hybrid transform and quantization with Huffman coding for video codec

Cited by 10 publications

References 3 publications

Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications

Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications

Research on Quantization Parameter Decision Scheme for High Efficiency Video Coding

H. 264 encoder using Gstreamer

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