Pixel value distributions of most real images have structure that cannot be modeled by simple and commonly used probability
distributions, such as Gaussian or log-normal distributions. Estimation of pixel value distribution in the joint measurement
space ( JMS ) of two real images reveals the joint density structure and allows its interpretation by means of
statistical dependence measures. A dependence measure is a general way to express similarity or divergence between
images. Candidate dependence measures include adaptations of information measures such as Shannon Entropy and
Fisher Information. The dependence measure built from Fisher Information is tested and demonstrated by experiments in
Independent Components Analysis ( ICA ) and co-registration of synthetic and real Landsat TM images, including successful
co-registration of images from different spectral bands with zero linear correlation.
The radiometric calibration of the two optical sensors on the Earth Observing One satellite has been studied as a function of time since launch. The calibration has been determined by ground reference calibrations at well-characterized field sites, such as White Sands Missile Range and dry playas, and by reference to other sensors such as the Enhanced Thematic Mapper Plus (ETM+) on Landsat 7. The ground reference calibrations of the Advanced Land Imager (ALI) give results consistent with the on-board solar calibrator and show a significant shift since preflight calibration in the short wavelength bands. Similarly, the ground reference calibrations of Hyperion show a change since preflight calibration, however, for Hyperion the largest changes are in the short wave infrared region of the spectrum. Cross calibration of ALI with ETM+ is consistent with the ground reference calibrations in the visible and near infrared. Results showing the changes in radiometric calibration are presented.