A simultaneous decomposition for three quaternion tensors with applications in color video signal processing

2020 ◽  
pp. 1-35
Author(s):  
Zhuo-Heng He ◽  
Chen Chen ◽  
Xiang-Xiang Wang
Keyword(s):  
Signal Processing ◽  
Video Signal ◽  
New Approach ◽  
Video Signal Processing ◽  
Encryption And Decryption ◽  
Color Video ◽  
The Given ◽  
Einstein Product

In this paper, we establish a simultaneous decomposition for three quaternion tensors via Einstein product. This simultaneous decomposition transforms the given three quaternion tensors into nice forms which have only 1 and 0. We conclude with an application in the color video signal processing. This new approach only need to store four keys to realize the simultaneous encryption and decryption of three videos.

Color video signal processing with median filters

1992 ◽  
Vol 38 (3) ◽  
pp. 157-161 ◽  
Author(s):  
H. Rantanen ◽  
M. Karlsson ◽  
P. Pohjala ◽  
S. Kalli
Keyword(s):  
Signal Processing ◽  
Video Signal ◽  
Median Filters ◽  
Video Signal Processing ◽  
Color Video

Characterizing Animal Behavior through Audio and Video Signal Processing

2007 ◽  
Vol 14 (4) ◽  
pp. 32-41 ◽  
Author(s):  
Dan Valente ◽  
Haibin Wang ◽  
Peter Andrews ◽  
Partha P. Mitra ◽  
Sigal Saar ◽  
...  
Keyword(s):  
Signal Processing ◽  
Animal Behavior ◽  
Video Signal ◽  
Video Signal Processing

Digital Time-Base Correction for Video Signal Processing

SMPTE Journal ◽  
1976 ◽  
Vol 85 (3) ◽  
pp. 146-150 ◽  
Author(s):  
David E. Acker ◽  
Richard H. Mclean
Keyword(s):  
Signal Processing ◽  
Video Signal ◽  
Time Base ◽  
Video Signal Processing ◽  
Digital Time

scholarly journals Data Association Methods via Video Signal Processing in Imperfect Tracking Scenarios: A Review and Evaluation

2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Hui Li ◽  
Yapeng Liu ◽  
Wenzhong Lin ◽  
Lingwei Xu ◽  
Junyin Wang
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
Data Association ◽  
Evaluation Criteria ◽  
Video Signal ◽  
Video Signal Processing ◽  
Video Signals ◽  
And Performance ◽  
Multiobject Tracking ◽  
Made In

In 5G scenarios, there are a large number of video signals that need to be processed. Multiobject tracking is one of the main directions in video signal processing. Data association is a very important link in tracking algorithms. Complexity and efficiency of association method have a direct impact on the performance of multiobject tracking. Breakthroughs have been made in data association methods based on deep learning, and the performance has been greatly improved compared with traditional methods. However, there is a lack of overviews about data association methods. Therefore, this article first analyzes characteristics and performance of three traditional data association methods and then focuses on data association methods based on deep learning, which is divided into different deep network structures: SOT methods, end-to-end methods, and Wasserstein metric methods. The performance of each tracking method is compared and analyzed. Finally, it summarizes the current common datasets and evaluation criteria for multiobject tracking and discusses challenges and development trends of data association technology and data association methods which ensure robust and real time need to be continuously improved.

A High Speed Digital Filter LSI for Video Signal Processing

1986 ◽  
Author(s):  
Masahide Abe ◽  
Hideki Kokubun ◽  
Tahito Aida ◽  
Katsuyuki Goto ◽  
Ki-ichi Kobayashi
Keyword(s):  
Signal Processing ◽  
Digital Filter ◽  
High Speed ◽  
Video Signal ◽  
Video Signal Processing
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