This paper presents a novel content-based image search and retrieval (CBIR) system that achieves coarse to fine remote sensing (RS) image description and retrieval in JPEG 2000 compressed domain. The proposed system initially: i) decodes the code-streams associated to the coarse (i.e., the lowest) wavelet resolution, and ii) discards the most irrelevant images to the query image that are selected based on the similarities estimated among the coarse resolution features of the query image and those of the archive images. Then, the code-streams associated to the sub-sequent resolution of the remaining images in the archive are decoded and the most irrelevant images are selected by considering the features associated to both resolutions. This is achieved by estimating the similarities between the query image and remaining images by giving higher weights to the features associated to the finer resolution while assigning lower weights to those related to the coarse resolution. To this end, t...
A novel coarse-to-fine remote sensing image retrieval system in JPEG-2000 compressed domain / Preethy Byju, Akshara; Demir, Begum; Bruzzone, Lorenzo. - 10789:(2018). ( Image and Signal Processing for Remote Sensing XXIV 2018 BERLIN 9-13 SEPTEMBER 2018) [10.1117/12.2327051].
A novel coarse-to-fine remote sensing image retrieval system in JPEG-2000 compressed domain
Preethy Byju, Akshara;Begum Demir;Lorenzo Bruzzone
2018-01-01
Abstract
This paper presents a novel content-based image search and retrieval (CBIR) system that achieves coarse to fine remote sensing (RS) image description and retrieval in JPEG 2000 compressed domain. The proposed system initially: i) decodes the code-streams associated to the coarse (i.e., the lowest) wavelet resolution, and ii) discards the most irrelevant images to the query image that are selected based on the similarities estimated among the coarse resolution features of the query image and those of the archive images. Then, the code-streams associated to the sub-sequent resolution of the remaining images in the archive are decoded and the most irrelevant images are selected by considering the features associated to both resolutions. This is achieved by estimating the similarities between the query image and remaining images by giving higher weights to the features associated to the finer resolution while assigning lower weights to those related to the coarse resolution. To this end, t...I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



