Name
Abstract | ||
|---|---|---|
This paper presents an adaptive and intelligent sparse model for digital image sampling and recovery. In the proposed sampler, we adaptively determine the number of required samples for retrieving image based on space-frequency-gradient information content of image patches. By leveraging texture in space, sparsity locations in DCT domain, and directional decomposition of gradients, the sampler str... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCI.2018.2833625 | IEEE Transactions on Computational Imaging |
Keywords | Field | DocType |
Discrete cosine transforms,Imaging,Image coding,Adaptation models,Image reconstruction,Automata,Sensors | Iterative reconstruction,Computer vision,Image processing,Digital image,Sparse image,Pixel,Sampling (statistics),Artificial intelligence,Compressed sensing,Mathematics,Nonuniform sampling | Journal |
Volume | Issue | ISSN |
4 | 3 | 2573-0436 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Taimori | 1 | 1 | 0.35 |
| Farokh Marvasti | 2 | 573 | 72.71 |