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Image and Graphics (ICIG), 2011 Sixth International Conference on

Date 12-15 Aug. 2011

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  • [Front cover]

    Publication Year: 2011 , Page(s): C1
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    Freely Available from IEEE
  • [Title page i]

    Publication Year: 2011 , Page(s): i
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  • [Title page iii]

    Publication Year: 2011 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2011 , Page(s): iv
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2011 , Page(s): v - xvi
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  • Preface

    Publication Year: 2011 , Page(s): xvii
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  • Conference organization

    Publication Year: 2011 , Page(s): xviii - xix
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  • Program Committee Members

    Publication Year: 2011 , Page(s): xx - xxiv
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  • Keynote Abstracts

    Publication Year: 2011 , Page(s): xxv - xxix
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (189 KB)  

    These keynote speeches discuss the following: Finding it Now: Stream Mining in Real Time; Patterns of Motion: Discovery and Generalized Representation; and 3D Structure Reconstruction from Videos. View full abstract»

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  • Tutorial abstract

    Publication Year: 2011 , Page(s): xxx - xxxi
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (211 KB)  

    Summary form only given, as follows. The goal of this tutorial is to provide the ICIG community with an introduction to the quickly developing area of low-rank matrix recovery. Low-rank (or approximately low-rank) matrices arise in a great number of applications involving image and video data. A few recurrent examples in this tutorial will include aligning batches of images, super-resolution and v... View full abstract»

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  • Workshop abstracts [3 abstracts]

    Publication Year: 2011 , Page(s): xxxii - xxxv
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (188 KB)  

    Provides an abstract for each of the three workshop presentations and a brief professional biography of each presenter. View full abstract»

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  • A Semi-automatic Method for Vascular Image Segmentation

    Publication Year: 2011 , Page(s): 3 - 7
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (768 KB) |  | HTML iconHTML  

    Vascular diseases are major public heath problem around the world. Vessel segmentation has been widely concerned because it is a key step for diagnosis and surgical planning. Among past strategies, multi-scale line filters are very popular detectors. However, multi-scale integration results in undesirable diffusion when two vessels are closely located. To avoid this problem, we use gradient vector... View full abstract»

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  • Exemplar-Based Image Inpainting with Collaborative Filtering

    Publication Year: 2011 , Page(s): 8 - 11
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (398 KB) |  | HTML iconHTML  

    This paper proposes a novel patch synthesis approach for exemplar-based propagation in image in painting. Currently, plural non-local exemplar patches synthesis is widely adopted to fill missing pixels. It generally provides good results, but sometimes shows poor visual quality due to dissimilarity between exemplars and targets. In this paper, a collaborative filtering approach is used to enhance ... View full abstract»

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  • A Unified Method Based on Wavelet Transform and C-V Model for Crack Segmentation of 3D Industrial CT Images

    Publication Year: 2011 , Page(s): 12 - 16
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (474 KB) |  | HTML iconHTML  

    Accurate segmentation of cracked body from three-dimensional (3D) industrial Computed Tomography (CT) images is an important step in the process of crack measurement and automatic recognition. In this paper we present a fast method for the segmentation of cracked body. The improved algorithm incorporates wavelet transform and Chan and Vese (C-V) model as key components. The 3D wavelet transform is... View full abstract»

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  • Multi-focus Image Fusion by Nonsubsampled Shearlet Transform

    Publication Year: 2011 , Page(s): 17 - 21
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1153 KB) |  | HTML iconHTML  

    In this paper we introduce the nonsubsampled shear let transform for multi-focus image fusion. In the proposed method, source images are decomposed by nonsubsampled shear let transform firstly. Then the decomposition coefficients are merged according to the given fusion rule. Finally the fused image is reconstructed by inverse nonsubsampled shear let transform. The experimental results over five p... View full abstract»

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  • Saliency Modulated High Dynamic Range Image Tone Mapping

    Publication Year: 2011 , Page(s): 22 - 27
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3399 KB) |  | HTML iconHTML  

    This paper presents a new high dynamic range image tone mapping technique - saliency modulated tone mapping (SMTM). The HDR image is not directly viewable and dynamic range compression will unavoidably loose information. A saliency map analyzes the visual importance of the regions and can therefore direct the tone mapping operators to preserve the visual conspicuity of the regions that should more... View full abstract»

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  • Locally Adaptive Shearlet Denoising Based on Bayesian MAP Estimate

    Publication Year: 2011 , Page(s): 28 - 32
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (485 KB) |  | HTML iconHTML  

    A locally adaptive Bayesian estimate for image denoising is proposed by exploiting the correlation among image shear let coefficients in a sub-band. The Laplacian distribution can model a wide range of process, from heavy-tailed to less heavy-tailed processes. This paper deduces Laplacian prior distribution based the MAP estimate formula and sub-band adaptive threshold. Finally, a simulation is ca... View full abstract»

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  • Integrating Boundary Cue with Superpixel for Image Segmentation

    Publication Year: 2011 , Page(s): 33 - 38
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1159 KB) |  | HTML iconHTML  

    This paper researches image segmentation as a global optimization problem and proposes a new way, which is called superpixel status model, to integrate boundary and region cue. Superpixel status model is a label model which describes the joint distribution of boundary and region classification in a Bayesian framework. For organizing a boundary classifier, the contour of super pixel is decomposed i... View full abstract»

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  • Integrating Low-level and Semantic Features for Object Consistent Segmentation

    Publication Year: 2011 , Page(s): 39 - 44
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (767 KB) |  | HTML iconHTML  

    The aim of semantic segmentation is to assign each pixel a semantic label. Numerous methods for semantic segmentation have been proposed in recent years and most of them chose pixel or super pixel as the processing primitives. However, as the information contained in a pixel or a super pixel is not discriminative enough, the outputs of these algorithms are usually not object consistent. To tackle ... View full abstract»

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  • A Fast Exact Euclidean Distance Transform Algorithm

    Publication Year: 2011 , Page(s): 45 - 49
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (554 KB) |  | HTML iconHTML  

    Euclidean distance transform is widely used in many applications of image analysis and processing. Traditional algorithms are time-consuming and difficult to realize. This paper proposes a novel fast distance transform algorithm. Firstly, mark each foreground's nearest background pixel's position in the row and column, and then use the marks scan the foreground area and figure out the first foregr... View full abstract»

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  • Reverse Seam Carving

    Publication Year: 2011 , Page(s): 50 - 55
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5372 KB) |  | HTML iconHTML  

    Seam carving is an effective operator supporting content-aware resizing for both image reduction and expansion. However, repeated seam removing and inserting processes lead to excessively distortion image when imposed on seam insertion then removal operations or the other way around. With considering the relationship between seam removing and inserting processes, we present an ameliorated energy f... View full abstract»

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  • Low Bit Rate Compression for SAR Image Based on Blocks Reordering and 3D Wavelet Transform

    Publication Year: 2011 , Page(s): 56 - 60
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1203 KB) |  | HTML iconHTML  

    Due to that there are a large number of similar characteristics in surface structure of the SAR image, a novel SAR image compression algorithm was proposed based on 3D wavelet transform after block reordering. This proposed algorithm consists of four successive steps: divide the image into sub-blocks with equal size, reorder the sub-blocks according to the similarity measured by weighted Euclidean... View full abstract»

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  • Distribution-Based Active Contour Model for Medical Image Segmentation

    Publication Year: 2011 , Page(s): 61 - 65
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1624 KB) |  | HTML iconHTML  

    Having being regarded as one of the classical methods in image segmentation, geodesic active contours (GAC) have the flaws of boundary leaking and expensive evolving time. In this paper, we present a distribution-based active contour model by measuring the Bhattacharyya distance between probability distributions of the object and background along with the evolution of GAC model. Due to combining t... View full abstract»

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  • Image Interpolation Using Autoregressive Model and Gauss-Seidel Optimization

    Publication Year: 2011 , Page(s): 66 - 69
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2198 KB) |  | HTML iconHTML  

    In this paper we propose a simple yet effective image interpolation algorithm based on autoregressive model. Unlike existing algorithms which rely on low resolution pixels to estimate interpolation coefficients, we optimize the interpolation coefficients and high resolution pixel values jointly from one optimization problem. Although the two sets of variables are coupled in the cost function, the ... View full abstract»

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  • Learning Based Adaptive Denoising Approach for Image Interpolation

    Publication Year: 2011 , Page(s): 70 - 75
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (414 KB) |  | HTML iconHTML  

    In this paper, we propose an effective image interpolation framework through learning based adaptive denoisng approach. In the local area, error pattern between original image and interpolated image is treated as stationary Gaussian distribution. Under the initial estimation, the proposed method apply the patch as the basic unit, in which Multiclass SVM classifier is used to determine iteration nu... View full abstract»

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