Flash LADAR systems are becoming increasingly popular for robotics applications. However, they generally
provide a low-resolution range image because of the limited number of pixels available on the focal plane array.
In this paper, the application of image super-resolution algorithms to improve the resolution of range data is
examined. Super-resolution algorithms are compared for their use on range data and the frequency-domain
method is selected. Four low-resolution range images which are slightly shifted and rotated from the reference
image are registered using Fourier transform properties and the super-resolution image is built using non-uniform
interpolation. Image super-resolution algorithms are typically rated subjectively based on the perceived visual
quality of their results. In this work, quantitative methods for evaluating the performance of these algorithms
on range data are developed. Edge detection in the range data is used as a benchmark of the data improvement
provided by super-resolution. The results show that super-resolution of range data provides the same advantage
as image super-resolution, namely increased image fidelity.
Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30 m), MODIS (500 m), and SeaWIFS (1000m).