A low-cost mechanical artifact is developed for the metrological verification of photogrammetric measurement systems. It is mainly composed of five delrin spheres and seven cubes manufactured in different sizes. A set of circular targets are fixed on these elements to perform the photogrammetric restitution. The artifact is used in order to compare three photogrammetric systems defined by three different cameras (Canon 5D with 14-mm lens, Nikon D200 with 20-mm lens, and Jai BB500GE with 8-mm lens). Photomodeler Pro and Matlab software are used for the data processing. The precision of the systems is evaluated using the standard deviation of the geometric coordinates calculated from the restitution of the circular targets. The accuracy is calculated using two different procedures: one of them uses the distance between the center of the spheres and the other uses the distance between the faces of the cubes. The comparison between the photogrammetric systems and their associated calibration files reveals that the Jai camera produces the best results in terms of precision and accuracy, while the Canon camera produces the poorest ones. The bad results from the Canon system are primarily related to the low quality of the calibration procedure.
We present a set of multiscale, multidirectional, rotation-invariant features for color texture characterization. The proposed model is based on the ranklet transform, a technique relying on the calculation of the relative rank of the intensity level of neighboring pixels. Color and texture are merged into a compact descriptor by computing the ranklet transform of each color channel separately and of couples of color channels jointly. Robustness against rotation is based on the use of circularly symmetric neighborhoods together with the discrete Fourier transform. Experimental results demonstrate that the approach shows good robustness and accuracy.
This paper concerns the study of visual impact assessment of routes on landscape by using remote sensing imagery. Basic indicators are created which can be useful for the analysis of route characteristics from the Landsat TM and Spot P fusion. The area which is the object of study is the Ancares Wildlife Reserve (Lugo, Spain). This paper focuses on the digital processing of rural roads to create indicators to determine if the road fits the landscape. Traditional methods are substituted by the application of satellite image processing through the application of linear enhancing, directional filtering, masking, supervised and unsupervised classifications and operations between images. A procedure has been developed which permits to map qualitative classes of visual integration of routes on landscape from the association of three variables: route linearity, vegetation in the roadside and visibility of the route. Fieldwork has allowed verification of the ground-truth between the physical reality of the area and the obtained thematic mapping. The information provided by the map will determine which routes require to take measures to reduce its visual impact on landscape.
Perceptual problems of viewing topography on geoimages are caused by illumination from the southeast during data collection. This problem affects the majority of satellite images. The aim of this work is to obtain a stereoscopic effect of shaded relief in such images. Techniques available in commercial digital processing programs are used in the absence of a digital elevation model. The images used are taken by the Landsat TM and SPOT P satellites; the software used was the EASI-PACE and ACE programs (Canadian PCI Geomatics Group). The pseudoscopic effect is solved by using the first principal component obtained in a principle components analysis of the three channels, resulting from the weighted merging of the Landsat and SPOT data. The map obtained provides the observer a view with shaded relief.
The perceptual problems of viewing topography on geo-images are caused by illumination from the southeast during data collecion. This problem affects the majority of satellite images. The aim f this work was to obtain a stereoscopic effect of shaded relief in such images. Techniques available in commercial digital processing programs were used in the absence of a digital elevation model. The images used were taken by the Landsat TM and SPOT P satellites; the software used was the EASI-PACE and ACE programs (Canadian PCI Geomatics Group). The pseudoscopic effect was solved by using the first principal component obtained in principle components analysis of the three channels resulting from the weighted merging of the Landsat and SPOT data. The map obtained provides the observer a view with shaded relief.
The extraction of man-made objects from remotely sensed imagery is a common application in remote sensing. Building detection is useful in territorial planning, mapping and Geographic Information Systems. Nevertheless these features are difficult to recognise in satellite data because of their variations in structure and size and especially because of the spatial resolution of the imagery. IRS panchromatic data, with 5,8 meters pixel size, was the higher spatial resolution sensor in civil applications until the Ikonos imageries distribution. Several approaches have been proposed for building detection in aerial images. Buildings cast a shadow in some direction and that is why many authors have employed shadows to detect constructions. Other authors use shadows to verify them, once they have been detected by some other techniques. This work focus on shadows detection probabilistic methods: it is found that digital supervised classification of the first principal component obtained from the application of a principal component analysis on the four channels of Ikonos allows identifying shadows and distinguishing them from other covers in the image. It is a fast and effective method and it can be implemented through tools available in commercial remote sensing software. This shadow detection system will provide cost-effectiveness in the inventorying of buildings, especially in areas of dispersed settlement, given that it significantly reduces fieldwork, and even can function as a support and test of the methods of automatic extraction of buildings from satellite images developed up to now.