Abstract
We present spatiotemporal denoising based on overlapped motion compensation and advanced collaborative filtering. First, noise-robust overlapped motion compensation is performed on a block basis for temporal grouping. Next, the K-nearest neighbors of each block are grouped in a 3D array, and the 3D array is transformed. Then, adaptive soft thresholding is performed in the 3D transform domain. In addition, a modified weighting strategy for aggregation is applied for better visual quality. Simulation results show that the proposed algorithm improves the peak signal-to-noise ratio performance by about 2 dB in comparison with the state-of-the-art technique while providing much better subjective visual quality.
| Original language | English |
|---|---|
| Article number | 023004 |
| Journal | Journal of Electronic Imaging |
| Volume | 21 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2012 |
Bibliographical note
Funding Information:This research was supported by the Defense Acquisition Program Administration and Agency for Defense Development of Korea through the Image Information Research Center at the Korea Advanced Institute of Science & Technology under UD100006CD. It was also supported by the Ministry of Knowledge Economy (MKE) and the Korea Institute for Advancement of Technology (KIAT) through the Human Resource Training Project for Strategic Technology, and it was supported by the Inha University Research Grant.