Image rendering by adaptive refinement
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Hierarchical Data Structures and Algorithms for Computer Graphics. Part I.
IEEE Computer Graphics and Applications
Multi-resolution video representation for parallel disk arrays
MULTIMEDIA '93 Proceedings of the first ACM international conference on Multimedia
User-Centered Video: transmitting video images based on the user's interest
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive display of very large textures
Proceedings of the conference on Visualization '98
A Multi-Resolution Relational Data Model
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Hologram-like transmission of pictures
The Visual Computer: International Journal of Computer Graphics
| Hi-index | 0.00 |
There is a growing need for people to browse through files of images such as satellite or medical photos, to determine which ones warrant further examination. Users located at some distance from the image archive often must use slow transmission links such as telephone lines. If an image is scanned out line-by-line, top-to-bottom, the user must often wait too long to determine whether the image is of any use. Using the Progressive Transmission Method, however, images are encoded so that during transmission the entire display shows a rough version of the image in 'fat pixels'. If the user wishes to see more detail, additional data is sent and used to refine these pixels, until the exact original image is seen. We report here on extensions of this method to the rich color imagery found in remote-sensing applications. A significant advance is the elimination of unworkably large look-up tables by using a single simple algorithm for performing the required encoding and decoding operations. The method is conceptualized in a 'transmission cone' context which assists a user in interacting with the system. The user can roam over large images, zoom to various levels of resolution, and cause specified subregions of interest in the image to fill in to full resolution, at a tremendous saving in time.