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Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)最新文献

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A wavelet-based statistical model for image restoration 基于小波的图像恢复统计模型
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-20 DOI: 10.1109/ICIP.2001.959087
Y. Wan, R. Nowak
{"title":"A wavelet-based statistical model for image restoration","authors":"Y. Wan, R. Nowak","doi":"10.1109/ICIP.2001.959087","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959087","url":null,"abstract":"We develop a wavelet-based statistical method a general class of image restoration problems. In this approach, a signal prior is set up by modeling the image wavelet coefficients as independent Gaussian mixture random variables. We first specify a uniform (non-informative) prior distribution on the mixing parameters, which leads to a simple and efficient iterative algorithm for MAP estimation. This algorithm is similar to the EM algorithm in that it alternates between a state estimation step and a maximization step. Moreover, we show that our algorithm converges monotonically to a local maximum of the posterior distribution. We next generalize the result to non-uniform priors and develop an efficient integer programming algorithm that enables a similar alternating optimization procedure.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114461620","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}
引用次数: 11
Statistical wavelet subband modelling for texture classification 纹理分类的统计小波子带建模
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958979
P. Hill, D. Bull, C. N. Canagarajah
{"title":"Statistical wavelet subband modelling for texture classification","authors":"P. Hill, D. Bull, C. N. Canagarajah","doi":"10.1109/ICIP.2001.958979","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958979","url":null,"abstract":"Simple wavelet and wavelet packet transforms have often been used for texture characterisation through the analysis of spatial-frequency content. However, most previous methods make no use of any statistical analysis of the transforms' subbands. A novel method is now presented for modelling the multivariate distributions of subband coefficients by considering spatially related coefficients. The Bhattacharya and divergence metrics are then used to produce an improved texture classification method for the application to content based image retrieval.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115004888","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}
引用次数: 4
Synthesis of directional texture based on multiresolution block sampling and constrained block movement 基于多分辨率块采样和约束块移动的定向纹理合成
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958565
Yue Yu, Jiebo Luo, C. W. Chen
{"title":"Synthesis of directional texture based on multiresolution block sampling and constrained block movement","authors":"Yue Yu, Jiebo Luo, C. W. Chen","doi":"10.1109/ICIP.2001.958565","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958565","url":null,"abstract":"The synthesis of directional texture is particularly challenging. We present a novel directional texture method based on our previously proposed multiresolution block sampling (MBS) and constrained block movement. First, we estimate the dominant direction of a given directional texture. Using a modified random movement-control set, we incorporate an additional directional constraint into our basic method to produce a new directional texture. A number of directional textures are used to show the effectiveness of this extended method.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115156706","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}
引用次数: 4
Adaptive algorithms for variable-complexity video coding 可变复杂度视频编码的自适应算法
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.959052
I. Richardson, Yafan Zhao
{"title":"Adaptive algorithms for variable-complexity video coding","authors":"I. Richardson, Yafan Zhao","doi":"10.1109/ICIP.2001.959052","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959052","url":null,"abstract":"Variable-complexity algorithms provide a means of managing the computational complexity of a software video CODEC. The reduction in computational complexity provided by existing variable-complexity algorithms depends on the video scene characteristics and is difficult to predict. A new approach to variable-complexity encoding is proposed. A variable-complexity DCT algorithm is adaptively updated in order to maintain a near-constant computational complexity. The adaptive update algorithm is shown to be capable of providing a significant, predictable, reduction in computational complexity with only a small loss of video quality. The proposed approach may be particularly useful for software-only video encoding, in applications where processing resources are limited.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115413345","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}
引用次数: 19
Morphological degradation models and their use in document image restoration 形态退化模型及其在文件图像恢复中的应用
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958986
Qigong Zheng, T. Kanungo
{"title":"Morphological degradation models and their use in document image restoration","authors":"Qigong Zheng, T. Kanungo","doi":"10.1109/ICIP.2001.958986","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958986","url":null,"abstract":"Document images undergo various degradation processes. Numerous models of these degradation processes have been proposed in the literature. In this paper we propose a model-based restoration algorithm. The restoration algorithm first estimates the parameters of a degradation model and then uses the estimated parameters to construct a lookup table for restoring the degraded image. The estimated degradation model is used to estimate the probability of an ideal binary pattern, given the noisy observed pattern. This probability is estimated by degrading noise-free document images and then computing the frequency of corresponding noise-free and noisy pattern pairs. This conditional probability is then used to construct a lookup table to restore noisy images. The impact of the restoration process is then quantified by computing the decrease in OCR word and character error rate. We find that given the estimated degradation model parameter values, the restoration algorithm decreases the character error rate by 16.1% and the word error rate by 7.35%. In some categories of degradation (e.g. model parameters that give rise to broken characters) there is a 41.5% reduction in character error rate and 20.4% reduction in word error rate.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115624535","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}
引用次数: 42
Confocal volume rendering of the thorax 胸部的共聚焦体积图
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958486
R. Summers, R. Mullick, S. Finkelstein, D. Schrump
{"title":"Confocal volume rendering of the thorax","authors":"R. Summers, R. Mullick, S. Finkelstein, D. Schrump","doi":"10.1109/ICIP.2001.958486","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958486","url":null,"abstract":"Confocal volume rendering is a recently described technique to perform segmentation-free rendering. It can be combined with other post-processing techniques to yield images with desirable features such as improved visualization of surface detail and reduced clipping of important anatomy. We show the first application (to our knowledge) of confocal volume rendering to imaging of the thorax. We demonstrate how confocal volume rendering can be used to reveal intrathoracic airways and lung masses.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124291033","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}
引用次数: 1
(Semi-)automatic recognition of microorganisms in water (半)自动识别水中微生物
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958043
K. Rodenacker, P. Gais, U. Jütting, B. Hense
{"title":"(Semi-)automatic recognition of microorganisms in water","authors":"K. Rodenacker, P. Gais, U. Jütting, B. Hense","doi":"10.1109/ICIP.2001.958043","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958043","url":null,"abstract":"The structure of biocenosis is a powerful indicator for the condition of and changes in the quality of the ecosystem. Identification and quantification of populations of microorganisms enables an assessment of the effect of any stressor on it. A method and some results are presented using automatic image acquisition, evaluation and recognition to ease the time consuming part of manual organism recognition and counting at the microscope.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116763655","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}
引用次数: 9
Multiple parametric motion model estimation and segmentation 多参数运动模型的估计与分割
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958648
R. Montoliu, F. Pla
{"title":"Multiple parametric motion model estimation and segmentation","authors":"R. Montoliu, F. Pla","doi":"10.1109/ICIP.2001.958648","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958648","url":null,"abstract":"This paper presents a motion estimation and segmentation algorithm based on multiple parametric model estimation that determines the a priori unknown number of motion models present in the data. The algorithm applies a quasi-simultaneous parametric model fitting method based on a general least square fitting. Some experiments are showed in order to demonstrate the results obtained using the proposed algorithm.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116990074","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}
引用次数: 13
Recognition of anatomically relevant objects with binary partition trees 基于二叉划分树的解剖相关物体识别
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958044
T. Blaffert
{"title":"Recognition of anatomically relevant objects with binary partition trees","authors":"T. Blaffert","doi":"10.1109/ICIP.2001.958044","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958044","url":null,"abstract":"In this paper we demonstrate the application of a binary partition tree to the watershed segmentation with graph merging. An adjacency graph is used to represent the regions found in a watershed transform, merging of these regions is required to combine these regions for further processing. Each node in the binary partition tree represents a larger region that results from the merging of two small regions. Starting from the root node, image areas of child nodes can successively be investigated whether they belong to a certain class of objects. In our application we are e.g. interested in finding anatomical objects such as skull, lung, or heart in an X-ray image. The outlined classification strategy considers only a few, relevant region combinations and thus permits the introduction of sophisticated classification rules without compromising overall computation time. The use of rules improves the recognition rate over simpler linear or box-type classifiers.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117132678","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}
引用次数: 5
A method to contrast enhancement of digital dense breast images aimed to detect clustered microcalcifications 一种旨在检测聚集性微钙化的数字致密乳腺图像对比度增强方法
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.959014
Fátima L. S. Nunes, H. Schiabel, R. H. Benatti, Ricardo C. Stamato, M. Escarpinati, C.E. Goes
{"title":"A method to contrast enhancement of digital dense breast images aimed to detect clustered microcalcifications","authors":"Fátima L. S. Nunes, H. Schiabel, R. H. Benatti, Ricardo C. Stamato, M. Escarpinati, C.E. Goes","doi":"10.1109/ICIP.2001.959014","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959014","url":null,"abstract":"Computer-aided diagnosis (CAD) schemes have been developed in many research centers to help the early detection of breast cancer. However, dense breast images are a challenge to CAD schemes due to the low contrast between structures of interest (such as microcalcifications-small size structures-which usually are associated to several breast tumors) and the background. This work describes a method to eliminate the background of a digitized mammogram image as well as two specific techniques to enhance the contrast in dense breast digital images as part of a CAD scheme under development in our group. The results indicate that these techniques can improve the performance of the scheme, and, thus, it can help in the early detection of breast cancer.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117338841","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}
引用次数: 8
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