This thesis is based on modifications performed on the U.S. Army TACOM (Tank Automotive Command, Warren, Michigan) Thermal Imaging Model (TTIM). It discusses the TTIM computer model of a staring thermal imaging sensor with respect to spatial nonuniformities. The spatial nonuniformities in a staring sensor is caused by fixed pattern noise or responsivity variations across the sensor. The objective of the thesis is to present the correction schemes for spatial nonuniformities present on a staring thermal imaging sensor and the data analysis of the corrections using flat field and bar chart targets of known temperatures. The signal-to-noise ratios (S/Ns) of the images will be calculated and measured before and after the correction. A simulated image after a one-point correction will be evaluated by comparison with an image from a real system using a platinum silicide thermal imaging sensor. The limits and assumptions of the simulation also will be discussed.

Reflectance and temperature of bare field soil were measured to determine the relationship between soil water content and spectral reflectance and temperature. Reflectance in the six reflective Thematic Mapper (TM) wavebands plus a 1.15 to 1.30 μm waveband (referred to as MMR5) was measured using a ground-based radiometer across a soil water gradient provided by a line source sprinkler system. Temperature was measured using a hand-held infrared thermometer. The results of this study show that TM band 7 reflectance (2.05-2.30 μm) provided improved estimates of surface soil water content (0-0.5 cm depth) over estimates using reflectance information from all seven TM bands. Good correlations were found between band ratio spectral indices of TM5/TM7, MMR5/TM7, and MMR5/TM5 and surface soil water content. A soil temperature normalization utilizing daily values of maximum vapor pressure deficit was found to provide improved estimates of soil water content to depths greater than 0.5 cm over estimates using other temperature normalizations.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 63-64).

With the rapid growth in infrared sensor technology and its drastic cost reduction, the potential of application of these imaging technologies in computer vision systems has increased. One potential application for IR imaging is depth from stereo. Discerning depth from stereopsis is difficult because the quality of un-cooled sensors is not sufficient for generating dense depth maps. In this thesis, we investigate the production of sparse disparity maps from un-calibrated infrared stereo images and agree that a dense depth field may not be attained directly from IR stereo images, but perhaps a sparse depth field may be obtained that can be interpolated to produce a dense/semi-dense depth field. In our proposed technique, the sparse disparity map is produced by a robust features-based stereo matching method capable of dealing with the problems of infrared images, such as low resolution and high noise; initially, a set of stable features are extracted from stereo pairs using the phase congruency model, which contrary to the gradient-based feature detectors, provides features that are invariant to geometric transformations. Then, a set of Log-Gabor wavelet coefficients at different orientations and frequencies is used to analyze and describe the extracted features for matching. The resulted sparse disparity map is then refined by triangular and epipolar geometrical constraints. In densifying the sparse map, a watershed transformation is applied to divide the image into several segments, where the disparity inside each segment is assumed to vary smoothly. The surface of each segment is then reconstructed independently by fitting a spline to its known disparities; Experiments on a set of indoor and outdoor IR stereo pairs lend credibility to the robustness of our IR stereo matching and surface reconstruction techniques and hold promise for low-resolution stereo images which don’t have a large amount of texture and local details.

With the rapid growth in infrared sensor technology and its drastic cost reduction, the potential of application of these imaging technologies in computer vision systems has increased. One potential application for IR imaging is depth from stereo. Discerning depth from stereopsis is difficult because the quality of un-cooled sensors is not sufficient for generating dense depth maps. In this thesis, we investigate the production of sparse disparity maps from un-calibrated infrared stereo images and agree that a dense depth field may not be attained directly from IR stereo images, but perhaps a sparse depth field may be obtained that can be interpolated to produce a dense/semi-dense depth field. In our proposed technique, the sparse disparity map is produced by a robust features-based stereo matching method capable of dealing with the problems of infrared images, such as low resolution and high noise; initially, a set of stable features are extracted from stereo pairs using the phase congruency model, which contrary to the gradient-based feature detectors, provides features that are invariant to geometric transformations. Then, a set of Log-Gabor wavelet coefficients at different orientations and frequencies is used to analyze and describe the extracted features for matching. The resulted sparse disparity map is then refined by triangular and epipolar geometrical constraints. In densifying the sparse map, a watershed transformation is applied to divide the image into several segments, where the disparity inside each segment is assumed to vary smoothly. The surface of each segment is then reconstructed independently by fitting a spline to its known disparities; Experiments on a set of indoor and outdoor IR stereo pairs lend credibility to the robustness of our IR stereo matching and surface reconstruction techniques and hold promise for low-resolution stereo images which don’t have a large amount of texture and local details.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Monique P. Fargues, Gamani Karunasiri. Includes bibliographical references (p. 135-136). Also available online.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 214-232). Available also in a digital version from Dissertation Abstracts.

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