Name
Abstract | ||
|---|---|---|
This paper describes a method to group and compress a set of similar images. A clustering algorithm is used to identify and group images that are similar enough to take advantage of inter-image redundancy reduction. The redundancy is reduced through subtraction by a representative image. Several clustering alternatives were tested, and four image data sets were experimented We were able to achieve 13% to 25% better compression performance than using JPEG2000 to code each image individually. |
Year | Venue | Keywords |
|---|---|---|
2005 | Vision '05: Proceedings of the 2005 International Conference on Computer Vision | partitional clustering, image compression, image similarity, root mean squared error, inter image redundancy |
Field | DocType | Citations |
Compression (physics),Block Truncation Coding,Pattern recognition,Computer science,Coding (social sciences),Artificial intelligence,Data compression | Conference | 9 |
PageRank | References | Authors |
0.81 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Clinton Nielsen | 1 | 29 | 2.45 |
| Xiaobo Li | 2 | 9 | 0.81 |
| Kevin Abma | 3 | 9 | 0.81 |