Universal Tree Source Coding Using Grammar-Based Compression

2019 ◽  
Vol 65 (10) ◽  
pp. 6399-6413 ◽  
Author(s):  
Moses Ganardi ◽  
Danny Hucke ◽  
Markus Lohrey ◽  
Louisa Seelbach Benkner
Keyword(s):  
Source Coding ◽  
Universal Tree

Semantic Source Coding for Flexible Lossy Image Compression

2007 ◽  
Author(s):  
Shashi Phoha ◽  
Mendel Schmiedekamp
Keyword(s):  
Image Compression ◽  
Source Coding

Bit-Plane Coding in Extractable Source Coding: optimality, modeling, and application to 360° data

2021 ◽  
pp. 1-1
Author(s):  
Fangping Ye ◽  
Navid Mahmoudian Bidgoli ◽  
Elsa Dupraz ◽  
Aline Roumy ◽  
Karine Amis ◽  
...  
Keyword(s):  
Source Coding ◽  
Bit Plane Coding ◽  
Bit Plane

scholarly journals Research on Secure Debugging Interaction of Sensor Nodes Based on Visible Light Communication

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 953 ◽  
Author(s):  
Yuanchu Yin ◽  
Jiefan Qiu ◽  
Zhiqiang Li ◽  
Mingsheng Cao
Keyword(s):  
Visible Light ◽  
Channel Coding ◽  
Sensor Node ◽  
Source Coding ◽  
Visible Light Communication ◽  
Propagation Characteristic ◽  
Transmission Efficiency ◽  
Sensor Nodes ◽  
Pulse Interval ◽  
Inaccessible Area

When a wireless sensor node’s wireless communication fails after being deployed in an inaccessible area, the lost node cannot be repaired through a debugging interaction that relies on that communication. Visible light communication (VLC) as a supplement of radio wave communication can improve the transmission security at the physical layer due to its unidirectional propagation characteristic. Therefore, we implemented a VLC-based hybrid communication debugging system (HCDS) based on VLC using smartphone and sensor node. For the system’s downlink, the smartphone is taken as the VLC gateway and sends the debugging codes to the sensor node by the flashlight. To improve the transmission efficiency of the downlink, we also propose a new coding method for source coding and channel coding, respectively. For the source coding, we analyze the binary instructions and compress the operands using bitmask techniques. The average compression rate of the binary structure reaches 84.11%. For the channel coding, we optimize dual-header pulse interval (DH-PIM) and propose overlapped DH-PIM (ODH-PIM) by introducing a flashlight half-on state. The flashlight half-on state can improve the representation capability of individual symbols. For the uplink of HCDS, we use the onboard LED of the sensor node to transmit feedback debugging information to the smartphone. At the same time, we design a novel encoding format of DH-PIM to optimize uplink transmission. Experimental results show that the optimized uplink transmission time and BER are reduced by 10.71% and 22%, compared with the original DH-PIM.

scholarly journals Lossless Source Coding in the Point-to-Point, Multiple Access, and Random Access Scenarios

2020 ◽  
Vol 66 (11) ◽  
pp. 6688-6722
Author(s):  
Shuqing Chen ◽  
Michelle Effros ◽  
Victoria Kostina
Keyword(s):  
Multiple Access ◽  
Source Coding ◽  
Random Access ◽  
Point To Point

scholarly journals Object-Based Approach for Adaptive Source Coding of Surveillance Video

2019 ◽  
Vol 9 (10) ◽  
pp. 2003 ◽  
Author(s):  
Tung-Ming Pan ◽  
Kuo-Chin Fan ◽  
Yuan-Kai Wang
Keyword(s):  
Linear Model ◽  
Video Transmission ◽  
Moving Objects ◽  
Source Coding ◽  
Video Quality ◽  
Surveillance Video ◽  
Surveillance Videos ◽  
Object Based ◽  
High Recognition Accuracy ◽  
Object Dynamics

Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurrence of large and fast-moving objects) is characterized statistically as a linear model. A regression algorithm that uses robust M-estimator statistics is proposed to construct the linear model with respect to different bitrates. The linear model is applied to predict the bitrate increment required to enhance video quality. A simulated wireless environment is set up to verify the proposed method under different wireless situations. Experiments with real surveillance videos of a variety of object dynamics are conducted to evaluate the performance of the method. Experimental results demonstrate significant improvement of streaming videos relative to both visual and quantitative aspects.

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