This dissertation describes the application of maximum entropy image restoration to envelope-detected ultrasonic sector scans. The maximum entropy restoration of the image of a point target (phantom) test object is shown to be superior to results obtained from the more familiar Wiener filter. The subsequent application of maximum entropy to an in-vivo clinical ultrasound image, however, illustrates the pitfalls associated with determining the relative merit of an ultrasonic image restoration technique from test object results alone. Since the resolution of sector scan images is substantially worse in the lateral (azimuthal) scan direction than the axial scan direction, the deconvolution filters described in this thesis were applied in the lateral direction only. The maximum entropy method is shown to have certain inherent advantages over linear frequency-domain techniques for the restoration of ultrasonic sector scan images. The positivity constraint inherent in the maximum entropy method is shown to produce restorations with substantially fewer oscillatory artifacts than those produced by Wiener filtering. In addition, the iterative nature of the maximum entropy algorithm is shown to be compatible with the restoration of the undersampled regions in the far field of sector scan images. The restoration of sector scan images is complicated by the spatially varying degradation associated with such images. A novel approach to the restoration of this class of image degradation is presented in this thesis. The widespread use of maximum entropy image restoration has been inhibited by the technique's demanding computational requirements. This problem can be alleviated by the use of high speed computer hardware, and the final chapters of this thesis describe the design and construction of a microcomputer-based array processor. The advantages inherent in the use of such hardware are demonstrated with reference to the maximum entropy restoration of ultrasonic images.

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Made available in DSpace on 2014-06-11T19:22:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2001-07-31Bitstream added on 2014-06-13T20:28:47Z : No. of bitstreams: 1 ros_ga_me_prud.pdf: 2774435 bytes, checksum: 01fc7a1a81db789b581d633e7cc0393c (MD5) / O projeto tem por finalidade integrar técnicas de Computação Gráfica com as de Fotogrametria para obter como resultado final a visualização 3D de uma imagem digital. A partir do DTM regular definido por pontos que se conectam formando uma malha triangular, a tonalização é aplicada triângulo-a-triângulo utilizando um modelo de iluminação, juntamente com o método de tonalização. Para tanto, é necessária a transformação das coordenadas do DTM para as coordenadas fotogramétricas, através da equação de colinearidade, e dessas para as correspondentes coordenadas digitais. Como estas coordenadas não coincidem com as coordenadas de pixel é necessário a aplicação de um método de reamostragem para obter os tons de cinza dos pontos transformados. Esses tons de cinza são usados pelo modelo de iluminação para calcular as intensidades de iluminação nos vértices do MDT, que por sua vez são utilizados pelo modelo de tonalização para tonalizar o MDT. Finalmente, um modelo de projeção é utilizado para obter a sensação 3D no plano 2D. Os resultados obtidos foram satisfatórios, apresentando similaridade entre os métodos de tonalização e a representação da superfície. / The main purpose of this research is to integrate techniques of both Computer Graphic and Photogrammetry, in order to obtain as a final result the 3D visualization of a digital image. Starting from regular DTM defined by points connected in such a way that they can form a triangular mesh, the shading is applied triangle-to-triangle using an illumination model, together with the shading method. First it is necessary to transform the DTM coordinates through photogrammetric coordinates or collinearity equation, and then the results to digital coordinates. As these last coordinates do not coincide with pixel coordinates, a resampling technique is needed to get gray levels of computed coordinates. The interpolated gray levels are the basic input of the illumination model, which in turn supplies illumination intensities for the shading method, allowing the DTM to be shaded. Finally, a projection model is used to obtain 3D sensation onto 2D plane. The obtained result was satisfactory, showing similarity between the methods of shading and surface rendering.