Name
Title | ||
|---|---|---|
Space-Time Quantization and Motion-Aligned Reconstruction for Block-Based Compressive Video Sensing. |
Abstract | ||
|---|---|---|
The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.3837/tiis.2016.01.019 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
Compressive video sensing,space-time quantization,motion-aligned reconstruction,median filter based prediction,multi-hypothesis prediction | Space time,Computer vision,Computer science,Artificial intelligence,Quantization (signal processing),Distributed computing | Journal |
Volume | Issue | ISSN |
10 | 1 | 1976-7277 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran Li | 1 | 1 | 0.68 |
| Hongbing Liu | 2 | 59 | 8.74 |
| Wei He | 3 | 1 | 1.37 |
| Xingpo Ma | 4 | 2 | 1.05 |