RASTER

The design, fabrication, and characterization of an ultrawideband (UWB) antenna for near-field microwave imaging of dielectric objects are presented together with the imaging setup. The focus is on an application in microwave breast tumor detection. The new antenna operates as a sensor with the following properties: 1) direct contact with the imaged body; 2) more than 90% of the microwave power is coupled directly into the tissue; 3) UWB performance; 4) excellent de-coupling from the outside environment; 5) small size; and 6) simple fabrication. The antenna characterization includes return loss, total efficiency, near-field directivity, fidelity, and group velocity. The near-field imaging setup employs planar aperture raster scanning. It consists of two antennas aligned along each other's boresight and moving together to scan two parallel apertures. The imaged object lies between the two apertures. With a blind de-convolution algorithm, the images are de-blurred. Simulation and experimental results confirm the satisfactory performance of the antenna as an UWB sensor for near-field imaging.

Areal interpolation between one partitioning of geographical space and another remains an important topic, particular in terms of population counts and related statistics which are often required in order to compute an incidence ratio. Despite numerous recent developments in intelligent areal interpolation methods, and studies that have demonstrated their clear advantage over simple areal weighting, there is little evidence to suggest widespread usage amongst the GIS user community. It is argued that to encourage greater uptake such methods must offer simplicity and convenience. Areal interpolation based on binary dasymetric mapping is conceptually simple, but examples to date tend to use information extracted from multi-spectral satellite imagery which limits its perceived convenience. This paper examines a simple method to extract equivalent information from a raster pixel map. It is shown to offer comparable areal interpolation performance at considerably less cost in terms of both time and complexity.

This paper discusses the application of digital terrain analysis modeling techniques to the parameterization of a semi-distributed hydrologic model. Most current techniques for deriving physiographic parameters in watershed analyses, including those using commercial geographic information systems (GIS), are tedious, costly and time consuming. The demands of these techniques result in them usually being limited in practical application to deriving parameters at only one level of detail or for only one set of subbasins. This paper presents a computerized interface (SLURPAZ) that was developed to combine the output of an established digital terrain analysis model (TOPAZ) with digital land cover data to derive all the necessary physiographic parameters required as input by a widely used semi-distributed hydrological model (SLURP). This interface makes it possible to derive physiographic parameters rapidly and accurately, at several different levels of detail and for varying numbers of sub-basins. This paper describes the methods by which the SLURPAZ interface integrates land cover data with the topographic parameters derived by TOPAZ from a digital elevation model (DEM). It also presents an example application of the interface to an intermediate-sized alpine basin in Yukon, Canada. Hydrological model outputs obtained using the computerized interface are compared with those obtained using manual techniques. Crown

Reduced-reference systems can predict in real-time the perceived quality of images for digital broadcasting, only requiring that a limited set of features, extracted from the original undistorted signals, is transmitted together with the image data. This paper uses descriptors based on the color correlogram, analyzing the alterations in the color distribution of an image as a consequence of the occurrence of distortions, for the reducedreference data. The processing architecture relies on a double layer at the receiver end. The first layer identifies the kind of distortion that may affect the received signal. The second layer deploys a dedicated prediction module for each type of distortion; every predictor yields an objective quality score, thus completing the estimation process. Computational-intelligence models are used extensively to support both layers with empirical training. The double-layer architecture implements a generalpurpose image quality assessment system, not being tied up to specific distortions and, at the same time, it allows us to benefit from the accuracy of specific, distortion-targeted metrics. Experimental results based on subjective quality data confirm the general validity of the approach.

It is difficult to generate raster Digital Elevation Models (DEMs) from terrain mass point data sets too large to fit into memory, such as those obtained by LIDAR. We describe prototype tools for streaming DEM generation that use memory and disk I/O very efficiently. From 500 million bare-earth LIDAR double precision points (11.2 GB) our tool can, in just over an hour on a standard laptop with two hard drives, produce a 50,394 × 30,500 raster DEM with 20 foot post spacing in 16 bit binary BIL format (3 GB), using less than 100 MB of main memory and less than 300 MB of temporary disk space.

Many statistical queries such as maximum likelihood estimation involve finding the best candidate model given a set of candidate models and a quality estimation function. This problem is common in important applications like land-use classification at multiple spatial resolutions from remote sensing raster data. Such a problem is computationally challenging due to the significant computation cost to evaluate the quality estimation function for each candidate model. For example, a recently proposed method of multi-scale, multi-granular classification has high computational overhead of function evaluation for various candidate models independently before comparison. In contrast, we propose an upper bound based context-inclusive approach that reduces computational overhead based on the context, i.e. the value of the quality estimation function for the best candidate model so far. We also prove that an upper bound exists for each candidate model and the proposed algorithm is correct. Experimental results using land-use classification at multiple spatial resolutions from satellite imagery show that the proposed approach reduces the computational cost significantly.

The development of a simple algorithm for deriving raster data from scanned thematic maps is described. Such maps usually contain extra information in addition to the thematic information—identification symbols and cartographic details—which need to be removed before the information can be used in a Geographic Information System. The method described here requires the user to identify those pixel values which represent unwanted information. The program then attempts to replace these with the thematic data values in the neighboring pixels. The method has been implemented as a module for the IDRISI raster GIS which runs on IBM PCs. The FORTRAN source is included, together with an explanation of some of the design decisions taken in writing it. Initial results from the method seem promising, although further work is required to determine the optimum method of scanning to use, and the types of maps for which the method is most suited.

Maps can be a great source of information for a given geographic region, but they can be difficult to find and even harder to process. A significant problem is that many interesting and useful maps are only available in raster format, and even worse many maps have been poorly scanned and they are often compressed with lossy compression algorithms. Furthermore, for many of these maps there is no meta data providing the geographic coordinates, scale, or projection. Previous research on map processing has developed ...

The variability of panchromatic and multispectral images, vector data (maps) and DEM models is growing. Accordingly, the requests and challenges are growing to correlate, match, co-register, and fuse them. Data to be integrated may have inaccurate and contradictory geo-references or not have them at all. Alignment of vector (feature) and raster (image) geospatial data is a difficult and time-consuming process when transformational relationships between the two are nonlinear. The robust solutions and commercial software products that address current challenges do not yet exist. In the proposed approach for Vector-to-Raster Registration (VRR) the candidate features are auto-extracted from imagery, vectorized, and compared against existing vector layer(s) to be registered. Given that available automated feature extraction (AFE) methods quite often produce false features and miss some features, we use additional information to improve AFE. This information is the existing vector data, but the vector data are not perfect as well. To deal with this problem the VRR process uses an algebraic structural algorithm (ASA), similarity transformation of local features algorithm (STLF), and a multi-loop process that repeats (AFE-VRR) process several times. The experiments show that it was successful in registering road vectors to commercial panchromatic and multi-spectral imagery.

Measuring the degree of similarity between thematic raster databases is a common task widely used in remote sensing accuracy assessment, spatial model validation, and many other geospatial tasks. However, conventional similarity measures look only at point-to-point similarity; they are not designed to evaluate the similarity of shapes and arrangements of features within the databases being compared. This study proposes a

This paper presents an efficient implementation of moving least square(MLS) approximation for 3D surface reconstruction. The smoothness of the MLS is mainly determined by the weight function where its support greatly affects the accuracy as well as the computational time in the mixed dense and scattered data. In a point-set, possibly acquired from a 3D scanning device, it is important to determine the support of the weight function adaptively depending on the distribution and shape of the given scatter data. Particulary in case of face data including the very smooth parts, detail parts and some missing parts of hair due to low reflectance, preserving some details while filling the missing parts smoothly is needed. Therefore we present a fast algorithm to estimate the support parameter adaptively by a raster scan method from the quantized integer array of the given data. Some experimental results show that it guarantees the high accuracy and works to fill the missing parts very well.

Misalignment between the color planes used to print color images creates undesirable artifacts in printed images. Color trapping is a technique used to diminish these artifacts. It consists of creating small overlaps between the color planes, either at the page description language level or the rasterized image level. Existing color trapping algorithms for rasterized images trap pixels independently. Once a pixel is trapped, the next pixel is processed without making use of the information already acquired. We propose a more efficient strategy which makes use of this information. Our strategy is based on the observation of some important properties of color edges. Combined with any existing algorithm for trapping rasterized images, this strategy significantly reduces its complexity. We implement this strategy in combination with a previously proposed color trapping algorithm (WBTA08). Our numerical tests indicate an average reduction of close to 38% in the combined number of multiplications, additions, and "if" statements required to trap a page, as compared with WBTA08 by itself.

We present an approach to perform geomorphometric analysis for Digital Elevation Models (DEM) to obtain the Cartographic Knowledge Domain (CKD) of the landscapes. CKD is oriented to represent the essential properties of DEM by means of concepts. These properties are obtained by analyzing the terrain topography. This analysis is based on two classifications: landform and topographic ruggedness. The approach involves the following raster layers: slope, profile curvature and plan curvature (primary attributes), which have been built to identify the intrinsic properties of the landscape. We use a multi-valued raster to integrate the primary attributes of DEM to generate the landform classification layer in order to find the terrain characteristics of the water movement. The topographic ruggedness is used to express the amount of elevation difference between adjacent cells of DEM. The topographic ruggedness is presented by means of Terrain Ruggedness Index (TRI). This work is oriented to support subsequent processes. The method has been implemented into Geographical Information System – ArcInfo, and applied for Tamaulipas State, Mexico.

PROGRAMS FOR RECORDING SEMANTIC DATA ON A RASTER MAP (AS EXEMPLIFIED BY TOURIST MAPS). "Recording semantic data on a raster map and thus making it amenable to reading through a browser has so far posed an unsolved problem. In numerous cases, such a new cartographic product would be an advantage over traditional cartographic GIS products. The advantage would be augmented by no need for a user to have specialized knowledge and command of GIS. The knowledge of geography at the secondary-school level would be sufficient to create and use such maps.
Long-term research on methods for recording semantic information on raster maps and on the use of other graphic documents in a raster form have resulted in developing methods for generating e-symbols based on the source alphabet.
To implement the method, the authors have developed a software package containing an analyzer, an e-symbol library generator, an editor for placing e-symbols on a raster map, and a graphic browser for reading the semantic information written on a raster map. The paper describes application of the software on a tourist map as an example.
The study is based on a map type that is commonly used by tourists, which contains mostly information on places worth visiting (historical and national monuments of architecture and nature), tourist trails (for pedestrians, bikers, cars), transportation system (bus stops, railway stations, ferry terminals), as well as on tourist infrastructure and entertainment (accommodation, restaurants, cinemas, bars, discos). The software described in the paper makes it possible to extend the information content of such a tourist map by any additional items (e.g., standard, address, phone number, and e-mail address of accommodation, geographical coordinates, etc.) without loss of clarity and without any need to build an extra database.
Flexibility of the method presented makes it possible to supplement the contents of such map by including any type of information important for the user.
Keywords: GIS, Raster Map, Semantic Data, Graphic Editor, Maps for Tourists.""

Emergent interactive technologies, such as tablet computers and smart-phones, and consumer demand for media forms to be available digitally for consumption through the internet, at any time and in any place has lead to a series of transformative changes in the ways we can read and interact with comics. With these changes come a series of difficulties and challenges in the ways comics are displayed on screen. It is these challenges in our reading of, and interaction with, digital comics that this study addresses through a critical evaluation of the required differences in presentation of the printed page and the screen "page". The focus of the study is on the use of double page spreads and how they can be adapted to the screen for an easier and less intrusive presentation or panels and their sequence.

METHOD AND SOFTWARE FOR CREATION OF RASTER INTERACTIVE  TOURIST MAPS WITH SEMANTIC INFORMATION ABOUT OBJECTS. "Reading map combines reading text signatures-and obtaining information in process of transition from cartographic model into a message in a language (verbal-numerical form). For GIS-user not only the information from traditional map is accessible, but also the information gathered and recorded in a semantic database. However printed GIS-map contains the same information as traditional map. All semantic data are stored in a database and cannot be read from a hard-copy. The problem which needs to be solved here is (he manner of attaching semantic data to raster map, in a way which allows putting such data in raster map and enables its reading from hard-copy. As the solution of problem mentioned above, the method of writing down" of semantic data in a raster map with use of symbols of the E-alphabet is described. These symbols guarantee
user an opportunity for reading the complete information included in G1S. The important stage in symbol of the E-alphabet generation is the choice of the basic alphabet. In the article results of research are presented and examples of maps for tourists.
KEYWORDS: GIS, Raster Map, Semantic Data, Graphic Editor, Maps for Tourists."

"Map reading combines reading text signatures and obtaining information in the process of transition from cartographic model into a message in a language (verbal-numerical form). For GlS-users not only the information from a traditional map is accessible, but also the information gathered and recorded in a semantic database. However, a printed GIS-map contains the same information as a traditional map. All semantic data are
stored in a database and cannot be read from a hard-copy. The problem which needs to be solved here is the manner of attaching semantic data to a raster map, in a way which allows putting such data in a raster map and enables its reading from a hard-copy. As a solution to the problem mentioned above, the method of writing semantic data in a raster map using symbols of the GIS-alphabet is described. These symbols guarantee the user the opportunity for reading the complete information included in die GIS. An important stage in the symbol of the GIS-alphabet generation is the choice of the basic alphabet. The methods of alphabet choice optimization are described in this article. The purpose of optimization is the minimization of the area needed for putting a symbol in a map, what results in practically unchanged legibility of the printed GIS-map (hard-copy) in comparison to the legibility of a traditional one.
Keywords: GIS, Raster Map, Semantic Data, GIS-Alphabet, Hard-Copy, Topographical Database."

TECHNOLOGY OF PREPARING RASTER MAPS WITH DESCRIPTIVE DATA OF POINTS OF INTEREST. "Tourist maps are one category of map designed for the mass user. For this reason this product needs to meet several requirements, e.g., it needs to be cheap, simple to use, easily and rapidly updated using a standard computer, navigation software and a mobile phone. The research presented in this paper, including e.g., the classification of points of interest, e-symbols as a tool to save descriptive data on raster maps, map editing software, and a browser for visualizing standard reports, forms the basis for a technology for creating interactive raster maps with descriptive data. Examples of preparing maps and their content show that the technology developed might be used for other thematic maps.
KEy words: SIP, map, raster, data, tourism.""""