| Multi-frame super-resolution by enhanced shift & add |
| English |
| Al Ismaeil, Kassem  [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >] |
| Aouada, D. [SnT - Universtity of Luxembourg, Luxembourg] |
| Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >] |
| Mirbach, B. [Advanced Engineering - IEE S.A., Contern, Luxembourg] |
| 2013 |
| International Symposium on Image and Signal Processing and Analysis, ISPA |
| IEEE Computer Society |
| 171-176 |
| Yes |
| International |
| 18455921 |
| 8th International Symposium on Image and Signal Processing and Analysis, ISPA 2013 |
| 4 September 2013 through 6 September 2013 |
| Trieste |
| [en] Motion estimation ; Pyramidal optical flow ; Super-resolution ; Upsampling ; Estimation ; Median filters ; Optimization ; Signal processing ; Signal sampling ; Accurate registration ; Initial estimation ; Initialization stage ; Median filtering ; Qualitative evaluations ; State-of-art methods ; Super resolution ; Up sampling ; Optical resolving power |
| [en] A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more robust and accurate registration as early as in the initialization stage of the high resolution estimate. Indeed, we solve the limitations on scale and motion inherent to the classical Shift & Add approach by upsampling the low resolution frames up to the super-resolution factor prior to estimating motion or to median filtering. This is followed by an appropriate selective optimization, leading to an enhanced Shift & Add. Quantitative and qualitative evaluations have been conducted at two levels; the initial estimation and the final optimized superresolution. Results show that the proposed algorithm outperforms existing state-of-art methods. © 2013 University of Trieste and University of Zagreb. |
| Chiron;DAVE;Esteco;Fimi - Barco;Fondazione CRTrieste;IEEE Signal Processing Society - Italian Chapter |
| http://hdl.handle.net/10993/26431 |
| 103279
9789531841948 |
