Earth Surface Recovery From Remotely Sensed Images

Jianping Wang; Ian R. Greenshields

doi:10.1117/12.949049

7 March 1989 Earth Surface Recovery From Remotely Sensed Images

Jianping Wang, Ian R. Greenshields

Proceedings Volume 1005, Optics, Illumination, and Image Sensing for Machine Vision III; (1989) https://doi.org/10.1117/12.949049
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

Conventional methods for the recovery of shape from shading assume homogeneity in the reflectance properties of the scene under analysis. However, imagery obtained from such sources as LANDSAT MSS or TM are usually comprised of regions of widely varying illumination characteristics. Given this, it follows that a single, non-partitioned approach to surface recovery from such images is almost always bound to fail. In this paper, we discuss a multifaceted approach to the problem of recovering surface features. We begin by classifying the image (through usual classificatory techniques) into distinct patches. For each of these surface types, a reflectance model is developed. This reflectance model is adjusted to coincide with the observed reflectance by the introduction of a reflectance remedy. This, in turn, leads to an image remedy equation. We then discuss an algorithm, which, under certain reasonable assumptions, will iteratively estimate the patch surface orientation, the reflectance remedy as well as the light source direction based on the equation developed.

Citation Download Citation

Jianping Wang and Ian R. Greenshields "Earth Surface Recovery From Remotely Sensed Images", Proc. SPIE 1005, Optics, Illumination, and Image Sensing for Machine Vision III, (7 March 1989); https://doi.org/10.1117/12.949049

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