Abstract :
A new method to decompose digital remotely sensed images is discussed in this paper. The information in the original remotely sensed data can be decomposed, pixel-by-pixel, into three components of natural light - solar direct illuminance (SDI), sky-scattering illuminance (SSI) and atmospheric path radiance (APR). Because the remotely sensed information is the result of the interaction between each component and ground features, the resultant component images of this method are more powerful than the original remotely sensed data in the quantitative inversion research of ground radiation energy, atmospheric environment condition, and remote sensing image pattern recognition
Keywords :
geophysical signal processing; image recognition; remote sensing; sky brightness; atmospheric environment condition; atmospheric path radiance; ground radiation energy; image decomposition; image pattern recognition; quantitative inversion research; remotely sensed digital image; sky-scattering illuminance; solar direct illuminance; Atmospheric waves; Brightness; Digital images; Frequency; Image analysis; Image decomposition; Pattern recognition; Remote sensing; Surface topography; USA Councils;
