Name
Title | ||
|---|---|---|
Lossless Image Compression Algorithm for Wireless Capsule Endoscopy by Content-Based Classification of Image Blocks. |
Abstract | ||
|---|---|---|
Recent advances in capsule endoscopy systems have introduced new methods and capabilities. The capsule endoscopy system, by observing the entire digestive tract, has significantly improved diagnosing gastrointestinal disorders and diseases. The system has challenges such as the need to enhance the quality of the transmitted images, low frame rates of transmission, and battery lifetime that need to be addressed. One of the important parts of a capsule endoscopy system is the image compression unit. Better compression of images increases the frame rate and hence improves the diagnosis process. In this paper a high precision compression algorithm with high compression ratio is proposed. In this algorithm we use the similarity between frames to compress the data more efficiently. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Compression (physics),Wireless,Pattern recognition,Computer science,Algorithm,Compression ratio,Artificial intelligence,Frame rate,Data compression,Capsule endoscopy,Image compression,Lossless compression |
DocType | Volume | Citations |
Journal | abs/1802.07781 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Atefe Rajaeefar | 1 | 0 | 0.34 |
| Ali Emami | 2 | 8 | 8.05 |
| S. M. R. Soroushmehr | 3 | 71 | 21.08 |
| Nader Karimi | 4 | 145 | 32.75 |
| Shadrokh Samavi | 5 | 233 | 38.99 |
| Kayvan Najarian | 6 | 262 | 59.53 |