Name
Title | ||
|---|---|---|
3-D Adaptive Sparsity Based Image Compression with Applications to Optical Coherence Tomography |
Abstract | ||
|---|---|---|
We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TMI.2014.2387336 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Compression, denoising, image reconstruction, ophthalmic imaging, optical coherence tomography, retina, sparse representation, tomography | Noise reduction,Computer vision,Compression (physics),Texture compression,Optical coherence tomography,Sparse approximation,Image coding,Transform coding,Artificial intelligence,Mathematics,Image compression | Journal |
Volume | Issue | ISSN |
PP | 99 | 0278-0062 |
Citations | PageRank | References |
4 | 0.42 | 33 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leyuan Fang | 1 | 639 | 33.52 |
| Shutao Li | 2 | 2594 | 139.10 |
| Xudong Kang | 3 | 451 | 22.68 |
| Joseph A Izatt | 4 | 36 | 3.14 |
| Sina Farsiu | 5 | 1723 | 77.49 |