Introduction to computer image processing

Theoretical backgrounds and digital techniques for a class of image processing problems are presented. Image formation in the context of linear system theory, image evaluation, noise characteristics, mathematical operations on image and their implementation are discussed. Various techniques for image restoration and image enhancement are presented. Methods for object extraction and the problem of pictorial pattern recognition and classification are discussed

DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces

Modeling the radiative behavior and the energy budget of land surfaces is relevant for many scientific domains such as the study of vegetation functioning with remotely acquired information. DART model (Discrete Anisotropic Radiative Transfer) is developed since 1992. It is one of the most complete 3D models in this domain. It simulates radiative transfer (R.T.) in the optical domain: 3D radiative budget and remote sensing images (i.e., radiance, reflectance, brightness temperature) of vegetation and urban Earth surfaces, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (flux tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. Here, its potential is illustrated with the case of urban and tropical forest canopies. Moreover, three recent improvements in terms of functionality and operability are presented: account of Earth/Atmosphere curvature for oblique remote sensing measurements, importation of 3D objects simulated as the juxtaposition of triangles with the possibility to transform them into 3D turbid objects, and R.T. simulation in landscapes that have a continuous topography and landscapes that are non repetitive. Finally, preliminary results concerning two application domains are presented. 1) 2D distribution of the reflectance, brightness temperature and radiance measured by a geostationary satellite over a whole continent. 2) 3D radiative budget of natural and urban surfaces with a DART energy budget (EB) component that is being developed. This new model, called DARTEB, is intended to simulate the energy budget of land surfaces

Utilizing radiation for smart robotic applications using visible, thermal, and polarization images.

The domain of this research is the use of computer vision methodologies in utilizing radiation for smart robotic applications for driving assistance. Radiation can be emitted by an object, reflected or transmitted. Understanding the nature and the properties of the radiation forming an image is essential in interpreting the information in that image which can then be used by a machine e.g. a smart vehicle to make a decision and perform an action. Throughout this work, different types of images are used to help a robotic vehicle make a decision and perform a certain action. This work presents three smart robotic applications; the first one deals with polarization images, the second one deals with thermal images and the third one deals with visible images. Each type of these images is formed by light (radiation) but in a way different from other types where the information embedded in an image depends on the way it was formed and how the light was generated. For polarization imaging, a direct method utilizing shading and polarization for unambiguous shape recovery without the need for nonlinear optimization routines is proposed. The proposed method utilizes simultaneously polarization and shading to find the surface normals, thus eliminating the reconstruction ambiguity. This can be useful to help a smart vehicle gain knowledge about the terrain surface geometry. Regarding thermal imaging, an automatic method for constructing an annotated thermal imaging pedestrian dataset is proposed. This is done by transferring detections from registered visible images simultaneously captured at day-time where pedestrian detection is well developed in visible images. Histogram of Oriented Gradients (HOG) features are extracted from the constructed dataset and then fed to a discriminatively trained deformable part based classifier that can be used to detect pedestrians at night. The resulting classifier was tested for night driving assistance and succeeded in detecting pedestrians even in the situations where visible imaging pedestrian detectors failed because of low light or glare of oncoming traffic. For visible images, a new feature based on HOG is proposed to be used for pedestrian detection. The proposed feature was augmented to two state of the art pedestrian detectors; the discriminatively trained Deformable Part based models (DPM) and the Integral Channel Features (ICF) using fast feature pyramids. The proposed approach is based on computing the image mixed partial derivatives to be used to redefine the gradients of some pixels and to reweigh the vote at all pixels with respect to the original HOG. The approach was tested on the PASCAL2007, INRIA and Caltech datasets and showed to have an outstanding performance

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop

This publication contains the summaries for the Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996. The main workshop is divided into two smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on March 4-6. The summaries for this workshop appear in Volume 1; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on March 6-8. The summaries for this workshop appear in Volume 2

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Simulation and Measurement of Multispectral Space Debris Light Curves

The accumulation of space debris has become one of the greatest threats facing the space industry to date. Through an increasing amount of objects deposited in Earth's orbit, such as rocket bodies, defunct satellites and general debris fragments, space missions are exposed to a growing risk of collisions. Moreover, the recent surge in commercial space applications is expected to further contribute to the problem. At the Institute of Technical Physics of Deutsches Zentrum für Luft- und Raumfahrt (DLR) in Stuttgart, resident space objects are monitored using a number of telescopes through active laser and passive sunlight illumination. Due to the high altitude and relatively small size of the objects they generally appear as unresolved points in photometric images. An object's temporal variation in brightness is referred to as a light curve and implies key information concerning the object's shape, material composition and rotation. Recovering these parameters from light signals is not trivial and it is anticipated that additional information provided by multispectral observations will contribute to a more reliable characterization of space debris. This research covers the development of a physically based simulation to model multispectral light reflections from space debris. The software is targeted towards ground-based observations and is expected to form an integral part in facilitating future strategies for comprehensive collision avoidance and space debris removal. Both passive light curves and laser ranging measurements are simulated using three-dimensional satellite models. To improve the accuracy of simulations, spectral lab measurements of common space materials are incorporated into the render. Further, the process of gathering reference measurements using the DLR's 43 cm telescope at the Uhlandshöhe Forschungsobservatorium is presented. For the comparison between synthetic and empirical light curves, a detailed calibration of the optical system is performed. The validity of the light curve simulator is confirmed the on the basis of recordings obtained from radar calibration targets. Finally, simulated data is used to study benefits of multispectral observations for characterization and parameter estimation from space debris

Earth resources: A continuing bibliography with indexes, issue 18

This bibliography lists 434 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1978. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis