The article presents an algorithm for three dimensional reconstruction of tomographic images based on reconstructed two dimensional slices, using a modification of the technique of additive algebraic reconstruction an...
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The article presents an algorithm for three dimensional reconstruction of tomographic images based on reconstructed two dimensional slices, using a modification of the technique of additive algebraic reconstruction and the spline function for interpolation of the intermediary planes in volumetric reconstruction. Development of the method was first destined to image reconstruction of the minitomographer at the National Center for Research and Instrumentation Development for Agriculture (CNPDIA) of the brazilian Agricultural Research Company (EMBRAPA), which is dedicated to soil science. Evaluation of the results of the method was based on phantom images and soil samples, with 2 mm spatial resolution, 60 samples per projection, a 3 degree angle between projections, a 59.9 KeV Americium (/sup 241/Am) energy source, and a ten second time per projection sample. The results prove the usefulness and reliability of the method, which is also applicable to other tomographic systems.
Diffusion and correlation effects are two principal phenomena which have been studied for years and several visualization techniques have been proposed to help scientists to understand them. The analysis of these phen...
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Diffusion and correlation effects are two principal phenomena which have been studied for years and several visualization techniques have been proposed to help scientists to understand them. The analysis of these phenomena will help to extract important information from data sets. To understand these problems we combine wavelet and entropy analysis to evaluate the evolution of these behaviours through scale and time. We present image case studies to show several different kinds of behaviours of these effects. Some of them are fallible cases and not reliable, as the images do not show the desired information. We calculate entropy of smooth and detail coefficient sets, generated by wavelet transform of these sample images in each scale, to obtain measures that allow us to evaluate these behaviours according to the organization complexity. These measures can provide an indication about the quality of the rendered images.
作者：
L.M.G. FonsecaM.H.M. CostaINPE
National Institute of Space Research (INPE) Sao Paulo Brazil UNICAMP
State University of Campinas Sao Paulo Brazil
image registration is one of the basic imageprocessing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-...
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image registration is one of the basic imageprocessing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity of the data, it is unlikely that a single registration scheme will work satisfactorily for all different applications. A possible solution is to integrate multiple registration algorithms into a rule-based artificial intelligence system, so that appropriate methods for any given set of multisensor data can be automatically selected. The objective of this paper is to present an automatic registration algorithm which has been developed at INPE. It uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The algorithm was tested on SPOT and TM images from forest, urban and agricultural areas. In all cases we obtained very encouraging results.
In this work, a morphological representation of a template matching algorithm for gray-scale images is presented. The algorithm is the composition of the so-called template matching operator with the maximum gray-leve...
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In this work, a morphological representation of a template matching algorithm for gray-scale images is presented. The algorithm is the composition of the so-called template matching operator with the maximum gray-level location operator, which can be both expressed in terms of the following classes of mathematical morphology elementary operators: dilations, erosions and anti-dilations. Moreover, the algorithm is applied to remote sensing images.
This paper presents an overview of the current state of the art in image fusion, with an emphasis on the emergence of new techniques, often issued from other domains like artificial intelligence and uncertainty modeli...
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This paper presents an overview of the current state of the art in image fusion, with an emphasis on the emergence of new techniques, often issued from other domains like artificial intelligence and uncertainty modeling. We address the two following points: firstly the aim of data fusion and its specificity when image information has to be combined, with emphasis on the respective roles of numerical and symbolic information, vs. numerical and symbolic types of treatment, secondly the theoretical frameworks for modeling imprecision and uncertainty (probability, fuzzy sets, belief functions). The main steps of image fusion are illustrated in a simple example in 3D medical image fusion.
Regular grids representing volume data are usually preferred to triangulation structures because they are simpler to store and faster to process. We consider here a special family of triangulations combining the flexi...
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Regular grids representing volume data are usually preferred to triangulation structures because they are simpler to store and faster to process. We consider here a special family of triangulations combining the flexibility of an adaptive representation of fields with some intrinsic regularity. We show that the projection algorithm to visualize scalar fields represented by adaptive square triangulations is far more efficient than to visualize general triangulations and it is competitive with regular grid visualization techniques.
The image alignment problem has as input a set of different images from a single object or several identical objects. One instance of the object in each image is misaligned relatively to the other in a given image, th...
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The image alignment problem has as input a set of different images from a single object or several identical objects. One instance of the object in each image is misaligned relatively to the other in a given image, that is, the objects lie in different positions and orientations. Thus, the problem consists in finding the homogeneous planar transforms for each of those instances. The process is not simple in the case of noisy images. Nevertheless, it is possible to tackle some cases of the image alignment problem using template matching. This work describes two methodologies that were developed to align noisy images of protein quaternary structures obtained by Transmission Electron Microscopy (TEM). These structures can be geometrically described by regular prisms and polyhedra. One of the methods uses the traditional approach for this problem-exploring image similarities. The second one explores the geometric simplicity of the objects being imaged by using template matching in order to solve the problem. The results show that there are cases where the template matching method achieves higher precision and computational efficiency to align that kind of image when compared to traditional ones.
In this paper we discuss the application of spatial-domain filters for solving the problem of automatic lane detection on gel electrophoresis computerimages. The problem can be posed as the determination of the numbe...
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In this paper we discuss the application of spatial-domain filters for solving the problem of automatic lane detection on gel electrophoresis computerimages. The problem can be posed as the determination of the number, location and orientation of lanes on the image, based on the analysis of their gray-level intensities. A novel iterative filtering algorithm is proposed based on the periodicity of image projection pattern. The algorithm is compared with clustering and frequency-domain filtering methods in terms of their effectiveness and efficiency from which a trade-off solution is presented.
This study presents an algorithm for three-dimensional reconstruction of tomographic images based on reconstructed two-dimensional slices, using a modification of the technique of additive algebraic reconstruction and...
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This study presents an algorithm for three-dimensional reconstruction of tomographic images based on reconstructed two-dimensional slices, using a modification of the technique of additive algebraic reconstruction and the spline function for interpolation of the intermediary planes in volumetric reconstruction. Development of the method was first destined to image reconstruction of the minitomographer at the National Center for Research and Instrumentation Development for Agriculture (CNPDIA) of the brazilian Agricultural Research Company (EMBRAPA), which is dedicated to soil science. Evaluation of the results of the method was based on phantom images and soil samples, with 2 mm spatial resolution, 60 samples per projection, a 3 degree angle between projections, a 59.9 KeV Americium (241 Am) energy source, and a ten-second time per projection sample. The results prove the usefulness and reliability of the method, which is also applicable to other tomographic systems.
In this paper we present a nonseparable complementary filter (CF) bank for image compression. We base our design of the filter bank on the two-dimensional (2D) multirate processing and on properties of complementary f...
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In this paper we present a nonseparable complementary filter (CF) bank for image compression. We base our design of the filter bank on the two-dimensional (2D) multirate processing and on properties of complementary filters. Perfect reconstruction is guaranteed when the CF bank is implemented with quincunx sampling and filtering, but not otherwise. In all cases, however the analysis and synthesis are performed without aliasing. The CF bank can be related to wavelet theory, permitting us to derive scale and wavelet functions for different sampling and filters. Examples illustrating the performance of the CF banks in image data compression are given.
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