Name
Abstract | ||
|---|---|---|
In this paper, a feature-based approach for automatic registration of NOAA AVHRR images is presented. The proposed approach makes use of the correlations between regions of the reference and sensed images both in feature and image spaces. The approach is summarized as follows: i) selection of potential control points in the reference image, automatically. Distinctive feature points with stronger edge energy than most of other pixels in reference image are selected as potential control points. ii) Finding for corresponding control points in the sensed image. The positions of corresponding control points in the sensed image are computed by means of feature matching using region similarity measures. iii) Mapping function estimation and transformation of the sensed image. Experimental results demonstrate that the proposed approach is capable of registering NOAA AVHRR images with high accuracy. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IGARSS.2006.256 | 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 |
Keywords | Field | DocType |
feature extraction, image registration, image match, remote sensing, NOAA AVHRR | Template matching,Feature detection (computer vision),Computer science,Remote sensing,Image processing,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Computer vision,Pattern recognition,Feature extraction,Distinctive feature,Pixel,Image registration | Conference |
Volume | Issue | ISSN |
null | null | 2153-6996 |
Citations | PageRank | References |
2 | 0.37 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiulin Lou | 1 | 4 | 1.82 |
| Weigen Huang | 2 | 6 | 6.76 |
| Bin Fu | 3 | 3 | 2.85 |
| Junhua Teng | 4 | 9 | 2.64 |