Compression faible complexité et codage par régions d’intérêt d’images fixes dans les WSNs (Low complexity image compression and region of interest coding in WSN)
| dc.contributor.author | MECHOUEK Khaoula | |
| dc.date.accessioned | 2022-12-14T12:37:57Z | |
| dc.date.available | 2022-12-14T12:37:57Z | |
| dc.date.issued | 2016-03-10 | |
| dc.description.abstract | Reducing the algorithmic complexity of image compression techniques is a great challenge in wireless image sensor networks (WISNs). Many image compression standards, such as JPEG and JPEG2000, are not suitable for implementation in WISNs because of its high energy consumption due to their high computational complexity. To solve the problem, in this thesis we proposed some low complexity image compression algorithms based on the discrete cosine transform (DCT) and the Discrete Tchebichef transform (DTT). Furthermore, we applied on them the pruned approach in order to more reduce its complexities and thence their energy consumption. Additionally, we proposed a region-of-interest based image compression using the DTT transform. Where, the main idea of this method is to compress certain parts of an image which are of a higher importance in detriment of the rest of the image. Simulation results show that the proposed compression methods require a reduced number of arithmetic operations, energy consumption and memory. And they have at the same time competitive compression efficiency compared with state-of-the-art image compression techniques which make them viable options for image compression and/or communication over WISNs. | |
| dc.identifier.uri | https://dspace.univ-annaba.dz//handle/123456789/800 | |
| dc.language.iso | en | |
| dc.title | Compression faible complexité et codage par régions d’intérêt d’images fixes dans les WSNs (Low complexity image compression and region of interest coding in WSN) | |
| dc.type | Thesis | |
| dspace.entity.type |