Space partitioning based image compression using quality measures for subdivision decision
| dc.contributor.author | Prasad M.V.N.K.; Mishra V.N.; Shukla K.K. | |
| dc.date.accessioned | 2025-05-24T09:58:22Z | |
| dc.description.abstract | This paper presents new partitioning methods for image compression using different image quality measures, which are improvements of the recently published Binary Tree Triangular Coding (BTTC) algorithm. The technique is based on recursive partitioning of the image domain into right-angled triangles arranged in a binary tree. All the partitioning methods proposed in this paper execute in O(n log n) time for encoding and θ(n) time for decoding, where n is the number of pixels in the image. Simulation results on standard test images show that the new methods produce significant improvement in quality as compared with conventional BTTC for comparable compression ratios. © 2003 Elsevier B.V. All rights reserved. | |
| dc.identifier.doi | https://doi.org/10.1016/S1568-4946(03)00039-5 | |
| dc.identifier.uri | http://172.23.0.11:4000/handle/123456789/23239 | |
| dc.relation.ispartofseries | Applied Soft Computing Journal | |
| dc.title | Space partitioning based image compression using quality measures for subdivision decision |