Graphical Models and Image Processing最新文献_第7页

Author Index for Volume 59 第59卷作者索引

Graphical Models and Image Processing Pub Date : 1997-11-01 DOI: 10.1006/gmip.1997.0458

引用次数: 0

New Algorithm for Medial Axis Transform of Plane Domain 平面域内轴线变换的新算法

Graphical Models and Image Processing Pub Date : 1997-11-01 DOI: 10.1006/gmip.1997.0444

Hyeong In Choi , Sung Woo Choi , Hwan Pyo Moon , Nam-Sook Wee

引用次数: 73

Contrast Enhancement via Image Evolution Flows 通过图像演化流的对比度增强

Graphical Models and Image Processing Pub Date : 1997-11-01 DOI: 10.1006/gmip.1997.0446

Guillermo Sapiro , Vicent Caselles

{"title":"Contrast Enhancement via Image Evolution Flows","authors":"Guillermo Sapiro , Vicent Caselles","doi":"10.1006/gmip.1997.0446","DOIUrl":"https://doi.org/10.1006/gmip.1997.0446","url":null,"abstract":"<div><p>A framework for contrast enhancement via image evolution flows and variational formulations is introduced in this paper. First, an algorithm for histogram modification via image evolution equations is presented. We show that the image histogram can be modified to achieve any given distribution as the steady state solution of this differential equation. We then prove that the proposed evolution equation solves an energy minimization problem. This gives a new interpretation to histogram modification and contrast enhancement in general. This interpretation is completely formulated in the image domain, in contrast with classical techniques for histogram modification which are formulated in a probabilistic domain. From this, new algorithms for contrast enhancement, including, for example, image and perception models, can be derived. Based on the energy formulation and its corresponding differential form, we show that the proposed histogram modification algorithm can be combined with image regularization schemes. This allows us to perform simulations contrast enhancement and denoising, avoiding common noise sharpening effects in classical schemes. Theoretical results regarding the existence of solutions to the proposed equations are presented.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 6","pages":"Pages 407-416"},"PeriodicalIF":0.0,"publicationDate":"1997-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0446","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92147685","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: 29

Nonparametric Estimation and Simulation of Two-Dimensional Gaussian Image Textures 二维高斯图像纹理的非参数估计与仿真

Graphical Models and Image Processing Pub Date : 1997-11-01 DOI: 10.1006/gmip.1997.0439

Thomas C.M. Lee , Mark Berman

{"title":"Nonparametric Estimation and Simulation of Two-Dimensional Gaussian Image Textures","authors":"Thomas C.M. Lee , Mark Berman","doi":"10.1006/gmip.1997.0439","DOIUrl":"https://doi.org/10.1006/gmip.1997.0439","url":null,"abstract":"<div><p>The work to be described is motivated by the need to simulate a variety of real–world image textures, all of which can be well approximated by stationary Gaussian random fields (SGRFs). Specifically, given an observed SGRF<em>T</em>, we wish to simulate SGRFs which look like and possess similar statistical properties to<em>T</em>. The main contribution of this paper is the development of an automatic and nonparametric spectrum estimation procedure which is able to produce an estimated spectrum of<em>T</em>in such a way that SGRFs simulated from this estimated spectrum have these desirable characteristics. Two special features of the procedure are: (i) it relies on a different risk function to that commonly used in nonparametric spectrum estimation, and (ii) it chooses its smoothing parameters by the technique of unbiased risk estimation. Results from a simulation study and a practical example demonstrate the good performance of the procedure. The practical example also illustrates how the proposed procedure can be combined with Monte Carlo testing to tackle target testing problems. Finally, the procedure is applied to the synthesis of some Brodatz textures, with some success.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 6","pages":"Pages 434-445"},"PeriodicalIF":0.0,"publicationDate":"1997-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92095448","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

REVIEWER ACKNOWLEDGMENT 评论家承认

Graphical Models and Image Processing Pub Date : 1997-11-01 DOI: 10.1006/gmip.1997.0457

引用次数: 0

On Digital Mammogram Segmentation and Microcalcification Detection Using Multiresolution Wavelet Analysis 基于多分辨率小波分析的数字乳房x线图像分割与微钙化检测

Graphical Models and Image Processing Pub Date : 1997-09-01 DOI: 10.1006/gmip.1997.0443

C.H. Chen , G.G. Lee

{"title":"On Digital Mammogram Segmentation and Microcalcification Detection Using Multiresolution Wavelet Analysis","authors":"C.H. Chen , G.G. Lee","doi":"10.1006/gmip.1997.0443","DOIUrl":"10.1006/gmip.1997.0443","url":null,"abstract":"<div><p>In this paper a multiresolution wavelet analysis (MWA) and nonstationary Gaussian Markov random field (GMRF) technique is introduced for the detection of microcalcifications with high accuracy. The hierarchical multiresolution wavelet information in conjunction with the contextual information of the images extracted from GMRF provides an efficient technique for microcalcification detection. A Bayesian learning paradigm realized via the expectation maximization (EM) algorithm was also introduced for edge detection or segmentation of mass regions recorded on the mammograms. The strength of the technique is in the effective utilization of the rich contextural information in the images considered. The effectiveness of the approach has been tested with a number of mammographic images for which the microcalcification detection algorithm achieved a sensitivity (true positive rate) of 94% and specificity (true negative rate) of 88%. Considerably good results were also obtained for the segmentation algorithm. In addition, the results for both the detected microcalcifications and the segmented mass regions were superimposed for an interesting case under the methods introduced.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 5","pages":"Pages 349-364"},"PeriodicalIF":0.0,"publicationDate":"1997-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0443","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114575575","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: 89

An Eigenspace Update Algorithm for Image Analysis 一种图像分析的特征空间更新算法

Graphical Models and Image Processing Pub Date : 1997-09-01 DOI: 10.1006/gmip.1997.0425

S. Chandrasekaran , B.S. Manjunath , Y.F. Wang , J. Winkeler , H. Zhang

{"title":"An Eigenspace Update Algorithm for Image Analysis","authors":"S. Chandrasekaran , B.S. Manjunath , Y.F. Wang , J. Winkeler , H. Zhang","doi":"10.1006/gmip.1997.0425","DOIUrl":"https://doi.org/10.1006/gmip.1997.0425","url":null,"abstract":"<div><p>During the past few years several interesting applications of eigenspace representation of images have been proposed. These include face recognition, video coding, and pose estimation. However, the vision research community has largely overlooked parallel developments in signal processing and numerical linear algebra concerning efficient eigenspace updating algorithms. These new developments are significant for two reasons: Adopting them will make some of the current vision algorithms more robust and efficient. More important is the fact that incremental updating of eigenspace representations will open up new and interesting research applications in vision such as active recognition and learning. The main objective of this paper is to put these in perspective and discuss a new updating scheme for low numerical rank matrices that can be shown to be numerically stable and fast. A comparison with a nonadaptive SVD scheme shows that our algorithm achieves similar accuracy levels for image reconstruction and recognition at a significantly lower computational cost. We also illustrate applications to adaptive view selection for 3D object representation from projections.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 5","pages":"Pages 321-332"},"PeriodicalIF":0.0,"publicationDate":"1997-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0425","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134836367","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: 0

Discrete Analytical Hyperplanes 离散解析超平面

Graphical Models and Image Processing Pub Date : 1997-09-01 DOI: 10.1006/gmip.1997.0427

Eric Andres , Raj Acharya , Claudio Sibata

引用次数: 126

Intrinsic Scale Space for Images on Surfaces: The Geodesic Curvature Flow 曲面上图像的内在尺度空间:测地线曲率流

Graphical Models and Image Processing Pub Date : 1997-09-01 DOI: 10.1006/gmip.1997.0442

Ron Kimmel

引用次数: 85

Geometric Shock-Capturing ENO Schemes for Subpixel Interpolation, Computation and Curve Evolution 几何冲击捕获ENO亚像素插值、计算和曲线演化

Graphical Models and Image Processing Pub Date : 1997-09-01 DOI: 10.1006/gmip.1997.0438

Kaleem Siddiqi , Benjamin B. Kimia , Chi-Wang Shu

{"title":"Geometric Shock-Capturing ENO Schemes for Subpixel Interpolation, Computation and Curve Evolution","authors":"Kaleem Siddiqi , Benjamin B. Kimia , Chi-Wang Shu","doi":"10.1006/gmip.1997.0438","DOIUrl":"10.1006/gmip.1997.0438","url":null,"abstract":"<div><p>Subpixel methods that locate curves and their singularities, and that accurately measure geometric quantities, such as orientation and curvature, are of significant importance in computer vision and graphics. Such methods often use local surface fits or structural models for a local neighborhood of the curve to obtain the interpolated curve. Whereas their performance is good in smooth regions of the curve, it is typically poor in the vicinity of singularities. Similarly, the computation of geometric quantities is often regularized to deal with noise present in discrete data. However, in the process, discontinuities are blurred over, leading to poor estimates at them and in their vicinity. In this paper we propose a geometric interpolation technique to overcome these limitations by locating curves and obtaining geometric estimates while (1) not blurring across discontinuities and (2) explicitly and accurately placing them. The essential idea is to avoid the propagation of information across singularities. This is accomplished by a one-sided smoothing technique, where information is propagated from the direction of the side with the “smoother” neighborhood. When both sides are nonsmooth, the two existing discontinuities are relieved by placing a single discontinuity, or shock. The placement of shocks is guided by geometric continuity constraints, resulting in subpixel interpolation with accurate geometric estimates. Since the technique was originally motivated by curve evolution applications, we demonstrate its usefulness in capturing not only smooth evolving curves, but also ones with orientation discontinuities. In particular, the technique is shown to be far better than traditional methods when multiple or entire curves are present in a very small neighborhood.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 5","pages":"Pages 278-301"},"PeriodicalIF":0.0,"publicationDate":"1997-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115973250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 88