Image databases are now currently utilized in a wide range of different areas, in particular, the development and application of remote sensing platforms result in the production of huge amounts of image data. One of the major problem in the practical implementation of a Content-based Image Retrieval (CBIR) for remotely sensed images is that the content-based indexing and searching process always requires extremely high computational power. On the other hand, the content-based image retrieval algorithms are very suitable for parallel computation as the algorithms can be broken into several data independent processes for running on a parallel computer. In this paper, we discuss the porting problem of a sequential application of remote sensed image retrieval in a parallel environment using the new paradigm of programming introduced by the birth of a new structured program languages (Assist 1.2) and compared performances to sequential and to commercial multiprocessors solutions.
|Titolo:||A Beowulf Class parallel remote-sensed image database retrieval system developed in ASSIST environment|
|Data di pubblicazione:||2005|
|Nome del convegno:||Conference on Storage and Retrieval Methods and Applications for Multimedia 2005|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1117/12.587981|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|