Application-Aware Approach to Compression and Transmission of H.264 Encoded Video for Automated and Centralized Transportation Surveillance

Chen, Zhaofu; Tsaftaris, Sotirios A.; Soyak, E.; Katsaggelos, Aggelos K.

doi:10.1109/tits.2013.2266861

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…A transportation video coding and wireless transmission system is presented and modifies the automated vehicle tracking applications. By considering the video characteristics and the lossy nature, video pre-processing is delivered and error control approaches are complemented in tracing the performance while bandwidth resources and computational power are conserved [18].…”

Section: Literature Surveymentioning

confidence: 99%

Enhanced Adaptive Approach of Video Coding at Very Low Bit Rate Using MSPIHT Algorithm

Ravichandran¹,

Malmurugan²

2016

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Nowadays video coding approach is a major key in many applications for easy transmission and storage consumption. The process of transformation is based on the empirical wavelet transform (EWT). The encoding process of video data provides secure and less consumption of storage and the reconstruction process consists of the reverse process with the extraction. In this paper, the coding of video is carried out at a very low bit rate with the enhancement of performance by proposing an approach of modified Set Partitioning in Hierarchical Tree (MSPIHT). This method encodes the high frequency frames with the scheduling of wavelet transform for efficient performances of encoding and improves the ability of both the frequency and time. By applying empirical wavelet transform on each video frame, the component of video frequency is extracted and the low frequency frame is encoded by the H.264/AVC standard. The low coefficient values are ignored in applying the threshold and in the reconstruction process, and HBLPCE method is used for imaging enhancement. The simulation of the proposed approach analysis shows better performance in reliable process and efficiency when compared to existing.

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Section: Literature Surveymentioning

confidence: 99%

Enhanced Adaptive Approach of Video Coding at Very Low Bit Rate Using MSPIHT Algorithm

Ravichandran¹,

Malmurugan²

2016

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“…Most of the work in ROI-based processing has focused on allocating more bits or higher transmission priority to the ROI. One study proposed a method for transmitting important data blocks through reliable wireless paths with higher priority [20], and another proposed a system that increases tracking accuracy while minimizing the data rate by concentrating bit allocation on the ROI [21]. While these approaches are intended to increase the efficiency of energy and bandwidth while preserving the quality of the ROI, they do not reduce the computation energy of the encoder since the entire region of the video should be processed at the encoder.…”

Section: Related Workmentioning

confidence: 99%

An Energy-Efficient Wireless Video Sensor Node for Moving Object Surveillance

Mudassar

Mukhopadhyay

2015

IEEE Trans. Multi-Scale Comp. Syst.

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In a wireless video sensor system, encoder and transmitter parameters should be jointly adjusted for the optimal tradeoff between video quality and energy consumption under variable channel conditions. The optimization of the system can be further enhanced by exploiting relative importance of moving objects in remote surveillance applications. This paper presents an energy-efficient wireless video sensor node for remote surveillance using content-aware pre-processing and an energy-and content-aware feedback control scheme. A low-overhead pre-processing engine detects the region of interest (ROI) in a frame defined as the macroblocks with moving objects, and an encoder selectively processes ROI macroblocks, resulting in reduction of both computation and transmission energy with minimum quality degradation of the ROI. We also propose an energy-and content-aware control scheme that jointly tunes the system parameters to maintain target transmission energy with minimum degradation of the ROI quality under varying wireless channel conditions. Compared to conventional encoding approaches, the proposed design consumes up to 56% less energy at the same quality.

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Function-Guided Energy-Precision Optimization with Precision-Rate-Complexity Bivariate Models

Líu

2018

Pattern Recognition and Computer Vision

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Application-Aware Approach to Compression and Transmission of H.264 Encoded Video for Automated and Centralized Transportation Surveillance

Cited by 5 publications

References 17 publications

Enhanced Adaptive Approach of Video Coding at Very Low Bit Rate Using MSPIHT Algorithm

Enhanced Adaptive Approach of Video Coding at Very Low Bit Rate Using MSPIHT Algorithm

An Energy-Efficient Wireless Video Sensor Node for Moving Object Surveillance

Function-Guided Energy-Precision Optimization with Precision-Rate-Complexity Bivariate Models

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