Method for noise suppressing edge enhancement based on genetic algorithm taking into account complexity of target images measured with fractal dimension is proposed. Through experiments with satellite remote sensing imagery data with additive noise, it is found that the proposed method shows appropriate edge enhancing performance with suppressing the additive noise in accordance with complexity...

This paper presents a morphological neural network approach to extract vehicle targets from high resolution panchromatic satellite imagery. In the approach, the morphological shared-weight neural network (MSNN) is used to classify image pixels on roads into vehicle targets and non-vehicle targets, and a morphology based preprocessing algorithm is developed to identify candidate vehicle pixels. ...

We present an application of our framework for 3-D object-centered change detection1–4 to combined satellite and aerial imagery . In this framework, geometry is compared to geometry, allowing us to compare image sets with different acquisition conditions and even different sensors. By working in this framework, we do not encounter the restrictions and short-comings of conventional image-based c...

This paper presents a practical method of epipolar resampling of high-resolution satellite imagery. Satellite imagery imaged with a linear array CCD sensor has quite different geometric characteristics from aerial photographs, therefore the conventional method of epipolar resampling is not applicable to it. On the other hand, epipolar resampling method based on rigorous orientation model with h...

The tidal wetlands within the Long Island Sound estuary serve a critical role in maintaining the health of the Sound. Over the past two centuries, there has been significant disturbance and loss of tidal wetlands along the Sound due primarily to anthropogenic activities. Researchers at the University of Connecticut and Wesleyan University are continuing on the second year of a two year project ...

Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown t...

Spectral similarity and spatial adjacency between various kinds of objects, shadow and occluded areas behind high rise objects as well as complex relationships lead to object recognition difficulties and ambiguities in complex urban areas. Using new multiangular satellite imagery, higher levels of analysis and developing a context aware system may improve object recognition results in these sit...

Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most ...

This study presents a new visualisation tool for classification of satellite imagery. Visualisation of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and u...

This themed issue focuses on the cultural meanings and spatial politics of high-resolution satellite imagery, critically examining how the burgeoning use of these data is radically reshaping the ways different groups comprehend space and place. Orbiting high overhead are a scatter of small, but very costly, satellites designed to produce streams of visual spatial representations of the ground b...