Model-based object recognition must solve three-dimensional geometric problems involving the registration of multiple sensors and the spatial relationship of a three-dimensional model to the sensors. Observation and verification of the registration and recognition processes requires display of these geometric relationships. We have developed a prototype software system which allows a user to in...

Aerial and satellite imagery are widely used to assess the severity and impact of wildfires. Light detection and ranging (LiDAR) is a newer remote sensing technology that has demonstrated utility in measuring vegetation structure. Combined use of imagery and LiDAR may improve the assessment of wildfire impacts compared to imagery alone. Estimation of tree mortality at the plot scale could serve...

We present a method to give single band intensified nightvision imagery a natural day-time color appearance. For input, the method requires a true color RGB source image and a grayscale nightvision target image. The source and target image are both transformed into a perceptually decorrelated color space. In this color space a best matching source pixel is determined for each pixel of the targe...

This paper presents a 3-D model-based ATR algorithm which operates simultaneously on imagery from three heterogeneous, approximately boresight aligned, sensors. An iterative search matches models to range and optical imagery by repeatedly predicting detectable features, measuring support for these features in the imagery, and adjusting the transformations relating the target to the sensors in o...

A new era of commercial high-resolution imagery from space began late in 1999 resulting in resolution that is now sufficient to resolve marine mammals. This encouraged investigating the use of satellite imagery for marine-mammal population census and related studies. The question was raised: Can marine mammals be reliably detected above sensor noise and ocean clutter? To answer this question, a...

QuickBird satellite imagery was evaluated for differentiating among rangeland cover types on the Welder Wildlife Refuge in south Texas. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Four subsets of the satellite image were extracted and used as study sites. Field spectral measurements made among the dominant vegetation types showed significant differences in...

We propose a new building detection and description algorithm for lidar data and photogrammetric imagery using directional histograms, splitting and merging segments, and line segments matching. Our algorithm consists of three steps. In the first step, we extract initial building regions from lidar data. Here, we apply a modified local maxima technique coupled with directional histograms and th...

A successful application of dense image matching algorithms to historical aerial photographs would offer a great potential for detailed reconstructions of historical landscapes in three dimensions, allowing for the efficient monitoring of various landscape changes over the last 50+ years. In this paper we propose the combination of image-based dense DSM (digital surface model) reconstruction fr...

Recent work has focused on generating synthetic imagery and augmenting real imagery to increase the size and variability of training data for learning visual tasks in urban scenes. This includes increasing the occurrence of occlusions or varying environmental and weather effects. However, few have addressed modeling the variation in the sensor domain. Unfortunately, varying sensor effects can d...

This paper presents a three-dimensional (3-D) model-based ATR algorithm that operates simultaneously on imagery from three heterogeneous, approximately boresight aligned sensors. An iterative search matches models to range and optical imagery by repeatedly predicting detectable features, measuring support for these features in the imagery, and adjusting the transformations relating the target t...