Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.559511
P. V. Roosmalen, S. Westen, R. Lagendijk, J. Biemond
Denoising images by means of thresholding transform coefficients has become popular. The discrete wavelet transform (DWT) seems to be very useful in this context. We propose a method for achieving a spatio-temporal decomposition of image sequences by combining the spacial Simoncelli (1992) pyramid with, in a temporal direction, wavelets. The directionally sensitive filter banks of the Simoncelli pyramid lead to better separation of signal and noise compared to a separable DWT. Including motion compensated temporal information further improves this separation. The directional sensitive filters also make it possible to locally estimate the amount of noise and the orientation of image structures. This information can be used to control the thresholding operation.
{"title":"Noise reduction for image sequences using an oriented pyramid thresholding technique","authors":"P. V. Roosmalen, S. Westen, R. Lagendijk, J. Biemond","doi":"10.1109/ICIP.1996.559511","DOIUrl":"https://doi.org/10.1109/ICIP.1996.559511","url":null,"abstract":"Denoising images by means of thresholding transform coefficients has become popular. The discrete wavelet transform (DWT) seems to be very useful in this context. We propose a method for achieving a spatio-temporal decomposition of image sequences by combining the spacial Simoncelli (1992) pyramid with, in a temporal direction, wavelets. The directionally sensitive filter banks of the Simoncelli pyramid lead to better separation of signal and noise compared to a separable DWT. Including motion compensated temporal information further improves this separation. The directional sensitive filters also make it possible to locally estimate the amount of noise and the orientation of image structures. This information can be used to control the thresholding operation.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122839601","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.560514
M. Gökmen, I. Ersoy, Anil K. Jain
We present an efficient model-based fingerprint image compression scheme based on a hybrid image model. Our model is based on extracting ridge and valley contours and then reconstructing a hybrid surface by using the gray values on these contours. The hybrid model we utilized is the convex combination of the membrane and plate functionals used for surface reconstruction by regularization. Two parameters of this model is determined to obtain a good approximation of the original fingerprint image given the sparse data, on ridges and valleys. In this compression scheme, the ridge contours are coded efficiently by using a differential chain code, while the differences between consecutive gray values along the chains are encoded using Huffman coding. Also included in the compressed image are the mean value of each valley segment and two parameters of the hybrid model. One advantage of our approach as compared to transform based algorithms and wavelet-based algorithms is that features such as delta and core points, end points, bifurcation points can be extracted directly from compressed image even for very high values of the compression ratio. The algorithm has been applied to various fingerprint images, and high compression ratios like 45:1 have been obtained while keeping all the important features in the images.
{"title":"Compression of fingerprint images using hybrid image model","authors":"M. Gökmen, I. Ersoy, Anil K. Jain","doi":"10.1109/ICIP.1996.560514","DOIUrl":"https://doi.org/10.1109/ICIP.1996.560514","url":null,"abstract":"We present an efficient model-based fingerprint image compression scheme based on a hybrid image model. Our model is based on extracting ridge and valley contours and then reconstructing a hybrid surface by using the gray values on these contours. The hybrid model we utilized is the convex combination of the membrane and plate functionals used for surface reconstruction by regularization. Two parameters of this model is determined to obtain a good approximation of the original fingerprint image given the sparse data, on ridges and valleys. In this compression scheme, the ridge contours are coded efficiently by using a differential chain code, while the differences between consecutive gray values along the chains are encoded using Huffman coding. Also included in the compressed image are the mean value of each valley segment and two parameters of the hybrid model. One advantage of our approach as compared to transform based algorithms and wavelet-based algorithms is that features such as delta and core points, end points, bifurcation points can be extracted directly from compressed image even for very high values of the compression ratio. The algorithm has been applied to various fingerprint images, and high compression ratios like 45:1 have been obtained while keeping all the important features in the images.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114154617","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.561018
Rosalind W. Picard, T. Minka, M. Szummer
In addition to the problem of which image analysis models to use in digital libraries, e.g. wavelet, Wold, color histograms, is the problem of how to combine these models with their different strengths. Most present systems place the burden of combination on the user, e.g. the user specifies 50% texture features, 20% color features, etc. This is a problem since most users do not know how to best pick the settings for the given data and search problem. The paper addresses this problem, describing research in progress for a system that: (1) automatically infers which combination of models best represents the data of interest to the user; and (2) learns continuously during interaction with each user. In particular, these two components-inference and learning-provide a solution that adapts to the subjective and hard to predict behaviors frequently seen when people query or browse image libraries.
{"title":"Modeling user subjectivity in image libraries","authors":"Rosalind W. Picard, T. Minka, M. Szummer","doi":"10.1109/ICIP.1996.561018","DOIUrl":"https://doi.org/10.1109/ICIP.1996.561018","url":null,"abstract":"In addition to the problem of which image analysis models to use in digital libraries, e.g. wavelet, Wold, color histograms, is the problem of how to combine these models with their different strengths. Most present systems place the burden of combination on the user, e.g. the user specifies 50% texture features, 20% color features, etc. This is a problem since most users do not know how to best pick the settings for the given data and search problem. The paper addresses this problem, describing research in progress for a system that: (1) automatically infers which combination of models best represents the data of interest to the user; and (2) learns continuously during interaction with each user. In particular, these two components-inference and learning-provide a solution that adapts to the subjective and hard to predict behaviors frequently seen when people query or browse image libraries.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114397598","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.560359
Oh-K. Kwon, D. Sim, Rae-Hong Park
A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper analyzes the conventional HD measures based on robust statistics, and proposes robust HD measures based on M-estimation, least trimmed square (LTS), and /spl alpha/-trimmed mean methods. The matching performance by the conventional and proposed HD measures is compared with synthetic and real images.
{"title":"New Hausdorff distances based on robust statistics for comparing images","authors":"Oh-K. Kwon, D. Sim, Rae-Hong Park","doi":"10.1109/ICIP.1996.560359","DOIUrl":"https://doi.org/10.1109/ICIP.1996.560359","url":null,"abstract":"A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper analyzes the conventional HD measures based on robust statistics, and proposes robust HD measures based on M-estimation, least trimmed square (LTS), and /spl alpha/-trimmed mean methods. The matching performance by the conventional and proposed HD measures is compared with synthetic and real images.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114458566","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.560608
Cormac Herley, P. Wong
We examine the problem of reconstructing a signal from periodic non-uniform samples, i.e. a uniform train from which samples are deleted in some periodic fashion. We develop the necessary and sufficient conditions for reconstruction, both for one and multiple dimensions. We prove that one-dimensional multiband signals which have arbitrary frequency support can be sampled without loss arbitrarily close to the theoretically minimum rate. An important advantage of our approach is the existence of an efficient design procedure for the reconstruction system. We show that the algorithm of projection on convex sets can be used to design the reconstruction filters efficiently. Once the filters are designed, the reconstruction algorithm is non-iterative. We give illustrative examples.
{"title":"Minimum rate sampling of signals with arbitrary frequency support","authors":"Cormac Herley, P. Wong","doi":"10.1109/ICIP.1996.560608","DOIUrl":"https://doi.org/10.1109/ICIP.1996.560608","url":null,"abstract":"We examine the problem of reconstructing a signal from periodic non-uniform samples, i.e. a uniform train from which samples are deleted in some periodic fashion. We develop the necessary and sufficient conditions for reconstruction, both for one and multiple dimensions. We prove that one-dimensional multiband signals which have arbitrary frequency support can be sampled without loss arbitrarily close to the theoretically minimum rate. An important advantage of our approach is the existence of an efficient design procedure for the reconstruction system. We show that the algorithm of projection on convex sets can be used to design the reconstruction filters efficiently. Once the filters are designed, the reconstruction algorithm is non-iterative. We give illustrative examples.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114500135","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.561020
C. Schmid, R. Mohr
The paper presents a general method to retrieve images from large databases using images as queries. The method is based on local characteristics which are robust to the group of similarity transformations in the image. Images can be retrieved even if they are translated, rotated or scaled. Due to the locality of the characterization, images can be retrieved even if only a small part of the image is given as well as in the presence of occlusions. A voting algorithm, following the idea of a Hough transform, and semi local constraints allow us to develop a new method which is robust to noise, to scene clutter and small perspective deformations. Experiments show an efficient recognition for different types of images. The approach has been validated on an image database containing 1020 images, some of them being very similar by structure, texture or shape.
{"title":"Image retrieval using local characterization","authors":"C. Schmid, R. Mohr","doi":"10.1109/ICIP.1996.561020","DOIUrl":"https://doi.org/10.1109/ICIP.1996.561020","url":null,"abstract":"The paper presents a general method to retrieve images from large databases using images as queries. The method is based on local characteristics which are robust to the group of similarity transformations in the image. Images can be retrieved even if they are translated, rotated or scaled. Due to the locality of the characterization, images can be retrieved even if only a small part of the image is given as well as in the presence of occlusions. A voting algorithm, following the idea of a Hough transform, and semi local constraints allow us to develop a new method which is robust to noise, to scene clutter and small perspective deformations. Experiments show an efficient recognition for different types of images. The approach has been validated on an image database containing 1020 images, some of them being very similar by structure, texture or shape.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121921130","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.559439
B. Aiazzi, P. S. Alba, S. Baronti, L. Alparone
In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the most effective progressive technique for inter-frame reversible compression of tomographic sections that typically occur in the medical field. An image sequence is decimated by a factor 2, first along rows only, then along columns only, and eventually along slices only, recursively in a sequel, thus creating a gray-level hyperpyramid whose number of voxels halves at every level. The top of the pyramid (root) is stored and then directionally interpolated by means of a 1D kernel. Interpolation errors with the underlying equally-sized hyperlayer are stored as well. The same procedure is repeated, until the image sequence is completely decomposed. The advantage of the novel scheme with respect to other noncausal DPCM schemes is twofold: firstly interpolation is performed from all error-free values, thereby reducing the variance of residuals; secondly different correlation values along rows, columns and sections can be exploited for a better decorrelation.
{"title":"Three-dimensional lossless compression based on a separable generalized recursive interpolation","authors":"B. Aiazzi, P. S. Alba, S. Baronti, L. Alparone","doi":"10.1109/ICIP.1996.559439","DOIUrl":"https://doi.org/10.1109/ICIP.1996.559439","url":null,"abstract":"In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the most effective progressive technique for inter-frame reversible compression of tomographic sections that typically occur in the medical field. An image sequence is decimated by a factor 2, first along rows only, then along columns only, and eventually along slices only, recursively in a sequel, thus creating a gray-level hyperpyramid whose number of voxels halves at every level. The top of the pyramid (root) is stored and then directionally interpolated by means of a 1D kernel. Interpolation errors with the underlying equally-sized hyperlayer are stored as well. The same procedure is repeated, until the image sequence is completely decomposed. The advantage of the novel scheme with respect to other noncausal DPCM schemes is twofold: firstly interpolation is performed from all error-free values, thereby reducing the variance of residuals; secondly different correlation values along rows, columns and sections can be exploited for a better decorrelation.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122113787","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.561026
Nicolas Chleq, M. Thonnat
This paper describes a generic framework for the realtime interpretation of video-surveillance scenes. The tool we have built according to this framework performs the understanding process up to the online recognition of ongoing scenario with respect to a library of scenario models dedicated to a particular application. This framework is currently applied for the European Esprit project PASSWORDS, the aim of which is to build a complete system for the automatic analysis and interpretation of video-surveillance image sequences.
{"title":"Realtime image sequence interpretation for video-surveillance applications","authors":"Nicolas Chleq, M. Thonnat","doi":"10.1109/ICIP.1996.561026","DOIUrl":"https://doi.org/10.1109/ICIP.1996.561026","url":null,"abstract":"This paper describes a generic framework for the realtime interpretation of video-surveillance scenes. The tool we have built according to this framework performs the understanding process up to the online recognition of ongoing scenario with respect to a library of scenario models dedicated to a particular application. This framework is currently applied for the European Esprit project PASSWORDS, the aim of which is to build a complete system for the automatic analysis and interpretation of video-surveillance image sequences.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116859301","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.560581
P. Salembier, F. Meyer, P. Brigger, Lionel Bouchard
This paper deals with the use of some morphological tools for video coding at very low bit rates. Rather than describing a complete coding algorithm, the purpose of this paper is to focus on morphological connected operators and segmentation tools that have proved to be attractive for compression.
{"title":"Morphological operators for very low bit rate video coding","authors":"P. Salembier, F. Meyer, P. Brigger, Lionel Bouchard","doi":"10.1109/ICIP.1996.560581","DOIUrl":"https://doi.org/10.1109/ICIP.1996.560581","url":null,"abstract":"This paper deals with the use of some morphological tools for video coding at very low bit rates. Rather than describing a complete coding algorithm, the purpose of this paper is to focus on morphological connected operators and segmentation tools that have proved to be attractive for compression.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116996889","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}
Pub Date : 1996-09-16DOI: 10.1109/ICIP.1996.560382
B. Ellerbroek, R. Plemmons
This work involves two-stage approaches to enhancing the quality of images taken through the atmosphere. First, a control problem arising in adaptive-optics is discussed. The problem involves optimal real-time control of very fast-acting deformable mirrors designed to compensate for atmospheric turbulence and other image degradation factors, such as wind-induced telescope vibration (windshake). The surface shapes of the mirrors must change rapidly to correct for time-varying optical distortions. The second stage of compensating for the effects of atmospheric turbulence generally occurs off-line, and consists of the post-processing step of image restoration. Here, the work involves large-scale computations, using either simultaneous image of a natural guide star or a large ensemble of images corresponding to different atmospheric realizations, to deconvolve the blurring effects of atmospheric turbulence.
{"title":"Computations in astro-imaging","authors":"B. Ellerbroek, R. Plemmons","doi":"10.1109/ICIP.1996.560382","DOIUrl":"https://doi.org/10.1109/ICIP.1996.560382","url":null,"abstract":"This work involves two-stage approaches to enhancing the quality of images taken through the atmosphere. First, a control problem arising in adaptive-optics is discussed. The problem involves optimal real-time control of very fast-acting deformable mirrors designed to compensate for atmospheric turbulence and other image degradation factors, such as wind-induced telescope vibration (windshake). The surface shapes of the mirrors must change rapidly to correct for time-varying optical distortions. The second stage of compensating for the effects of atmospheric turbulence generally occurs off-line, and consists of the post-processing step of image restoration. Here, the work involves large-scale computations, using either simultaneous image of a natural guide star or a large ensemble of images corresponding to different atmospheric realizations, to deconvolve the blurring effects of atmospheric turbulence.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129505005","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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