Image registration is a basic and troublesome assignment where managing remotely sensed satellite images. The registration of different platform images has turned into a critical issue with an expanding number of images gathered each day from various satellites. There exist an extensive variety of registration strategies for various kinds of utilizations and information sources, however no calculation is exact for enrolling multisource images reliably. This exploration tends to this issue by examining the advancement of a completely automatic registration system for an extremely confused issue of multisensor remote detecting images particularly Synthetic aperture radar (SAR) and electrooptical images. The development of this automatic image registration method is based on the extraction and matching of common features that are visible in both images. The algorithm involves the following five steps: noise removal, edge extraction, edge linking, pattern extraction and pattern matching to collect automatically the Ground Control Points (GCPs) required to the image registration. The application of the developed automatic image registration model to different SAR and optical image pairs showed that accurate ground control points (GCPs) could be identified automatically.
(2019). A Region Growing controlled by Edge Map technique (RGCE) for Automatic Registration of Satellite Images. Journal of the ACS Advances in Computer Science, 10(1), 113-125. doi: 10.21608/asc.2020.157433
MLA
. "A Region Growing controlled by Edge Map technique (RGCE) for Automatic Registration of Satellite Images". Journal of the ACS Advances in Computer Science, 10, 1, 2019, 113-125. doi: 10.21608/asc.2020.157433
HARVARD
(2019). 'A Region Growing controlled by Edge Map technique (RGCE) for Automatic Registration of Satellite Images', Journal of the ACS Advances in Computer Science, 10(1), pp. 113-125. doi: 10.21608/asc.2020.157433
VANCOUVER
A Region Growing controlled by Edge Map technique (RGCE) for Automatic Registration of Satellite Images. Journal of the ACS Advances in Computer Science, 2019; 10(1): 113-125. doi: 10.21608/asc.2020.157433