The problem of determining the approximate orientation of an object from multiview models is considered for the case in which the number of models if fixed but the viewing angles are arbitrary. The multiview models include the height and width of each projected image of a 3D object, topological information based on the edge image, some region information and the angles of each projected image. Assuming there is only one object being considered, an image is input in an arbitrary viewing direction (camera focal length and the distance between the camera and the object are known) and processed to obtain the edge image. The edge image coordinate data are transformed into normalized data with respect to focal length and distance. The height and width of the object are compared with the models' height and width to determine a set of candidates, and topological and region information are used for further matching to detect the approximate orientation. In their experiment the authors built the multiview models from 16 viewing angles, each roughly equal to 22.5 degrees .<>
{"title":"A method of detecting 3D object orientation by multiview models","authors":"G. Qu, S. L. Wood","doi":"10.1109/MDSP.1989.97003","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97003","url":null,"abstract":"The problem of determining the approximate orientation of an object from multiview models is considered for the case in which the number of models if fixed but the viewing angles are arbitrary. The multiview models include the height and width of each projected image of a 3D object, topological information based on the edge image, some region information and the angles of each projected image. Assuming there is only one object being considered, an image is input in an arbitrary viewing direction (camera focal length and the distance between the camera and the object are known) and processed to obtain the edge image. The edge image coordinate data are transformed into normalized data with respect to focal length and distance. The height and width of the object are compared with the models' height and width to determine a set of candidates, and topological and region information are used for further matching to detect the approximate orientation. In their experiment the authors built the multiview models from 16 viewing angles, each roughly equal to 22.5 degrees .<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121681516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. Interlaced scanning is an effective method of bandwidth compression that was appropriate in the old days when television frame memories were expensive. However, in addition to the loss of vertical resolution, interlacing results in many well-known artifacts (e.g. interline flicker, line crawl). Some novel techniques for reducing the artifacts associated with interlacing, and for effectively increasing the vertical resolution by motion-compensated interpolation are reported. Unlike motion-compensated coding, where inaccurate motion estimates only increase the bit rate slightly, and since motion-compensated interpolation has to be done entirely at the receiver, a hybrid pel recursive block matching technique is used for motion estimation, and additional postprocessing is used to remove any artifacts.<>
{"title":"Motion compensated deinterlacing of video sequences","authors":"F.-M. Wang, D. Anastassiou, A. Netravali","doi":"10.1109/MDSP.1989.97138","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97138","url":null,"abstract":"Summary form only given. Interlaced scanning is an effective method of bandwidth compression that was appropriate in the old days when television frame memories were expensive. However, in addition to the loss of vertical resolution, interlacing results in many well-known artifacts (e.g. interline flicker, line crawl). Some novel techniques for reducing the artifacts associated with interlacing, and for effectively increasing the vertical resolution by motion-compensated interpolation are reported. Unlike motion-compensated coding, where inaccurate motion estimates only increase the bit rate slightly, and since motion-compensated interpolation has to be done entirely at the receiver, a hybrid pel recursive block matching technique is used for motion estimation, and additional postprocessing is used to remove any artifacts.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122674512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. An estimator that can maintain acceptable performance for the hard conditions on which the maximum-likelihood estimator fails, i.e. when the signal-to-noise ratio falls below a certain threshold, is derived by introducing the prior information into the estimation. The prior information may be the approximate signal powers and the noise power. Because the available prior information is always vague, a robust way to incorporate it is developed. Simulation results showing the significant performance improvement are given.<>
{"title":"A robust estimator for direction finding with hierarchical prior","authors":"Q. Wu, D. Fuhrmann","doi":"10.1109/MDSP.1989.97078","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97078","url":null,"abstract":"Summary form only given. An estimator that can maintain acceptable performance for the hard conditions on which the maximum-likelihood estimator fails, i.e. when the signal-to-noise ratio falls below a certain threshold, is derived by introducing the prior information into the estimation. The prior information may be the approximate signal powers and the noise power. Because the available prior information is always vague, a robust way to incorporate it is developed. Simulation results showing the significant performance improvement are given.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133437609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. A parallel specification has been obtained for the opening and closing operations in image morphology in one and several dimensions. This has been done for the usual image case as well as in the wraparound case. The role of mathematical morphology in determining other multidimensional algorithms has also been identified. For instance, Mellin convolution is easily found by first utilizing the dilation operation. All the algorithms have been expressed using data-flow type diagrams and allow straightforward use of fault-tolerant methods. The unified signal algebra approach to parallel algorithms and architecture design has been used in developing all the procedures reported. It permits the design of data-flow systolic and wavefront array architectures.<>
{"title":"Parallel algorithm in image morphology","authors":"C. Giardina","doi":"10.1109/MDSP.1989.97089","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97089","url":null,"abstract":"Summary form only given. A parallel specification has been obtained for the opening and closing operations in image morphology in one and several dimensions. This has been done for the usual image case as well as in the wraparound case. The role of mathematical morphology in determining other multidimensional algorithms has also been identified. For instance, Mellin convolution is easily found by first utilizing the dilation operation. All the algorithms have been expressed using data-flow type diagrams and allow straightforward use of fault-tolerant methods. The unified signal algebra approach to parallel algorithms and architecture design has been used in developing all the procedures reported. It permits the design of data-flow systolic and wavefront array architectures.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133589673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. The use of stereo vision is significantly simplified by using depth information computed from a narrow-baseline image pair to constrain the search for correspondence in wider-baseline images. Such images can be acquired by using a combination of motion and multiple cameras. This approach has been in terms of random field models and Bayesian estimation. Experimental results have demonstrated the success of the approach. Algorithms that are efficient, produce accurate depth maps, and impose fewer constraint on scene geometry than previous approaches to stereo have been obtained and demonstrated with images of a realistic, outdoor scene model. The algorithms were developed as part of a larger scenario in which small camera motions will be used to bootstrap stereo correspondence.<>
{"title":"Bootstrap algorithms for dynamic stereo vision","authors":"L. Matthies, M. Okutomi","doi":"10.1109/MDSP.1989.96990","DOIUrl":"https://doi.org/10.1109/MDSP.1989.96990","url":null,"abstract":"Summary form only given. The use of stereo vision is significantly simplified by using depth information computed from a narrow-baseline image pair to constrain the search for correspondence in wider-baseline images. Such images can be acquired by using a combination of motion and multiple cameras. This approach has been in terms of random field models and Bayesian estimation. Experimental results have demonstrated the success of the approach. Algorithms that are efficient, produce accurate depth maps, and impose fewer constraint on scene geometry than previous approaches to stereo have been obtained and demonstrated with images of a realistic, outdoor scene model. The algorithms were developed as part of a larger scenario in which small camera motions will be used to bootstrap stereo correspondence.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134551499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. A novel scheme for image compression is proposed. Wavelet transform is used to obtain a set of orthonormal subclasses of images. Wavelets are functions that allow the construction of an orthonormal basis of L/sup 2/(R). The wavelet functions are well localized both in the space and frequency domains. The original image is decomposed on this orthonormal basis with a pyramidal algorithm architecture using quadrature mirror filters. This classification approach separates images (vectors) into perceptually distinct classes and thus matches the visual system model. The wavelet coefficients of each class are then vector quantized. The algorithm is based on a clustering approach and on the minimization of a distortion measure such as mean-squared error (MSE). A global codebook design unfortunately results in edge smoothing.<>
{"title":"Wavelet transform image coding using vector quantization","authors":"M. Barlaud, P. Mathieu, M. Antonini","doi":"10.1109/MDSP.1989.97056","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97056","url":null,"abstract":"Summary form only given. A novel scheme for image compression is proposed. Wavelet transform is used to obtain a set of orthonormal subclasses of images. Wavelets are functions that allow the construction of an orthonormal basis of L/sup 2/(R). The wavelet functions are well localized both in the space and frequency domains. The original image is decomposed on this orthonormal basis with a pyramidal algorithm architecture using quadrature mirror filters. This classification approach separates images (vectors) into perceptually distinct classes and thus matches the visual system model. The wavelet coefficients of each class are then vector quantized. The algorithm is based on a clustering approach and on the minimization of a distortion measure such as mean-squared error (MSE). A global codebook design unfortunately results in edge smoothing.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133874701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. A vector quantization (VQ) algorithm that utilizes this interblock correlation is proposed. Despite its usefulness for low bit-rate applications, the standard, table-lookup VQ has the drawback of exponential growth of both storage and computation requirements with vector dimension. In practice, the vector size is typically from 3*3 to 5*5. With this size, it has been found that there is still strong correlation between neighboring blocks. Experiments have shown that the approach generally gives better coding performance than previously designed VQ codes. So far, experimental results for coding various digital images are in the range of 30 dB to 36 dB with about 0.5 b.p.p.<>
{"title":"A conditional entropy-coded multi-stage vector quantizer for image coding","authors":"X. Yuan, V. Ingle","doi":"10.1109/MDSP.1989.97137","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97137","url":null,"abstract":"Summary form only given. A vector quantization (VQ) algorithm that utilizes this interblock correlation is proposed. Despite its usefulness for low bit-rate applications, the standard, table-lookup VQ has the drawback of exponential growth of both storage and computation requirements with vector dimension. In practice, the vector size is typically from 3*3 to 5*5. With this size, it has been found that there is still strong correlation between neighboring blocks. Experiments have shown that the approach generally gives better coding performance than previously designed VQ codes. So far, experimental results for coding various digital images are in the range of 30 dB to 36 dB with about 0.5 b.p.p.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123197217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. The phase retrieval problem is the problem of reconstructing a two-dimensional signal f(x,y) from measurements of its Fourier magnitude mod F(u, nu ) mod . The iterative algorithm of Fienup, a modification of the Gerchberg-Saton alternating projections algorithm, works reasonably well for real signals f(x,y)<0 that have compact support. However, the algorithm tends to stagnate, since the projections are not onto convex sets. The most difficult stagnations to escape have stripes running through the image. These stripes are more than just an artifact of the algorithm; they seem to be a fundamental difficulty, and a considerable amount of work has gone into studying ways of avoiding the stripes stagnation (other stagnations are much easier to escape). An approach that has successfully avoided stripes stagnations in numerical testing is reported.<>
{"title":"Avoiding phase-retrieval algorithm stagnation using the zeros of the Fourier magnitude","authors":"C. Wackerman, A. Yagle","doi":"10.1109/MDSP.1989.97116","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97116","url":null,"abstract":"Summary form only given. The phase retrieval problem is the problem of reconstructing a two-dimensional signal f(x,y) from measurements of its Fourier magnitude mod F(u, nu ) mod . The iterative algorithm of Fienup, a modification of the Gerchberg-Saton alternating projections algorithm, works reasonably well for real signals f(x,y)<0 that have compact support. However, the algorithm tends to stagnate, since the projections are not onto convex sets. The most difficult stagnations to escape have stripes running through the image. These stripes are more than just an artifact of the algorithm; they seem to be a fundamental difficulty, and a considerable amount of work has gone into studying ways of avoiding the stripes stagnation (other stagnations are much easier to escape). An approach that has successfully avoided stripes stagnations in numerical testing is reported.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121686518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given. Matching approaches are considered, and the problems with correlation matching, namely how the size and shape of the window and the property of the correlation function are selected and the high cost of searching for the maximum in the detectable region, are discussed. A highly efficient matching method that addresses these problems is discussed.<>
{"title":"The new advance on matching the gray value corners in image sequences","authors":"J. Li, S. Sang","doi":"10.1109/MDSP.1989.96991","DOIUrl":"https://doi.org/10.1109/MDSP.1989.96991","url":null,"abstract":"Summary form only given. Matching approaches are considered, and the problems with correlation matching, namely how the size and shape of the window and the property of the correlation function are selected and the high cost of searching for the maximum in the detectable region, are discussed. A highly efficient matching method that addresses these problems is discussed.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125402585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary form only given, as follows. The Heisenberg group and its representation theory plays an important role in the theory of Gabor expansions, ambiguity functions and Wigner distributions and wavelets built from translations in time and frequency. A multiplicative Heisenberg group whose representation theory can be used to study affine group wavelets and wideband ambiguity functions is defined. The standard Zac transform can be interpreted as an intertwining operator between two unitary representations of the Heisenberg group. A multiplicative Zac transform that plays an analogous role for the multiplicative Heisenberg group is constructed.<>
{"title":"Wavelets: a general overview","authors":"L. Auslander","doi":"10.1109/MDSP.1989.97050","DOIUrl":"https://doi.org/10.1109/MDSP.1989.97050","url":null,"abstract":"Summary form only given, as follows. The Heisenberg group and its representation theory plays an important role in the theory of Gabor expansions, ambiguity functions and Wigner distributions and wavelets built from translations in time and frequency. A multiplicative Heisenberg group whose representation theory can be used to study affine group wavelets and wideband ambiguity functions is defined. The standard Zac transform can be interpreted as an intertwining operator between two unitary representations of the Heisenberg group. A multiplicative Zac transform that plays an analogous role for the multiplicative Heisenberg group is constructed.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130841389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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