Publications

This paper reports on a novel approach to atmospheric cloud segmentation from a space based multi-spectral pushbroom satellite system. The satellite collects 15 spectral bands ranging from visible, 0.45 urn, to long wave in fared (IR), 10.7um. The images are radiometrically calibrated and have ground sample distances (GSD) of 5 meters for visible to very near IR bands and a GSD of 20 meters for near IR to long wave IR. The algorithm consists of a hybrid-classification system in the sense that supervised and unsupervised networks are used in conjunction. For performance evaluation, a series of numerical comparisons to human derived cloud borders were performed. A set of 33 scenes were selected to represent various climate zones with different land cover from around the world. The algorithm consisted of the following. Band separation was performed to find the band combinations which form significant separation between cloud and background classes. The potential bands are fed into a K-Means clustering algorithm in order to identify areas in the image which have similar centroids. Each cluster is then compared to the cloud and background prototypes using the Jeffries-Matusita distance. A minimum distance is found and each unknown cluster is assigned to their appropriate prototype. A classification rate of 88% was found when using one short wave IR band and one midwave IR band. Past investigators have reported segmentation accuracies ranging from 67% to 80%, many of which require human intervention. A sensitivity of 75% and specificity of 90% were reported as well.

Abstract not provided.

Hadamard Transform Spectrometer (HTS) approaches share the multiplexing advantages found in Fourier transform spectrometers. Interest in Hadamard systems has been limited due to data storage/computational limitations and the inability to perform accurate high order masking in a reasonable amount of time. Advances in digital micro-mirror array (DMA) technology have opened the door to implementing an HTS for a variety of applications including fluorescent microscope imaging and Raman imaging. A Hadamard transform spectral imager (HTSI) for remote sensing offers a variety of unique capabilities in one package such as variable spectral and temporal resolution, no moving parts (other than the micro-mirrors) and vibration tolerance. Two approaches to for 2D HTS systems have been investigated in this LDRD. The first approach involves dispersing the incident light, encoding the dispersed light then recombining the light. This method is referred to as spectral encoding. The other method encodes the incident light then disperses the encoded light. The second technique is called spatial encoding. After creating optical designs for both methods the spatial encoding method was selected as the method that would be implemented because the optical design was less costly to implement.

Abstract not provided.

The ultimate limitation in obtainable resolution and sensitivity for space-based imaging systems is the size of the optical collecting aperture. Large collecting apertures are at odds with maintaining low launch costs and with current launch vehicle configurations. Development of a deployable mirror is one approach being considered to satisfy these conflicting requirements. The focus of this research is to develop fundamental technology toward the realization of deployable electron-gun-controlled piezoelectric thin films mirrors as shown below. A bimorph layer of film will bend in response to an applied electric field and can therefore be deformed into desirable shapes using a scanning electron gun. Surface curvature measurements govern the electron gun scanning strategy, yielding distributed shape corrections.