A Characterization of Ten Hidden-Surface Algorithms
ACM Computing Surveys (CSUR)
Texture and reflection in computer generated images
Communications of the ACM
Illumination for computer generated pictures
Communications of the ACM
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Aerial Images to 3-D Terrain Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Approaches to Image Understanding
ACM Computing Surveys (CSUR)
Derivation of invariant scene characteristics from images
AFIPS '80 Proceedings of the May 19-22, 1980, national computer conference
Automatic determination of image-to-database correspondences
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
ACS'10 Proceedings of the 10th WSEAS international conference on Applied computer science
| Hi-index | 48.22 |
A number of image analysis tasks can benefit from registration of the image with a model of the surface being imaged. Automatic navigation using visible light or radar images requires exact alignment of such images with digital terrain models. In addition, automatic classification of terrain, using satellite imagery, requires such alignment to deal correctly with the effects of varying sun angle and surface slope. Even inspection techniques for certain industrial parts may be improved by this means.We achieve the required alignment by matching the real image with a synthetic image obtained from a surface model and known positions of the light sources. The synthetic image intensity is calculated using the reflectance map, a convenient way of describing surface reflection as a function of surface gradient. We illustrate the technique using LANDSAT images and digital terrain models.