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Image Processing, IEEE Transactions on

Issue 10 • Date Oct. 2013

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Displaying Results 1 - 25 of 45
  • Front Cover

    Publication Year: 2013 , Page(s): C1
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  • IEEE Transactions on Image Processing publication information

    Publication Year: 2013 , Page(s): C2
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  • Table of contents

    Publication Year: 2013 , Page(s): 3731 - B3733
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  • [Blank page]

    Publication Year: 2013 , Page(s): B3734
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  • Table of contents

    Publication Year: 2013 , Page(s): 3735 - B3738
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  • Non-Uniform Deblurring in HDR Image Reconstruction

    Publication Year: 2013 , Page(s): 3739 - 3750
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (4437 KB) |  | HTML iconHTML  

    Hand-held cameras inevitably result in blurred images caused by camera-shake, and even more so in high dynamic range imaging applications where multiple images are captured over a wide range of exposure settings. The degree of blurring depends on many factors such as exposure time, stability of the platform, and user experience. Camera shake involves not only translations but also rotations result... View full abstract»

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  • Towards Online Iris and Periocular Recognition Under Relaxed Imaging Constraints

    Publication Year: 2013 , Page(s): 3751 - 3765
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2007 KB) |  | HTML iconHTML  

    Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a ran... View full abstract»

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  • Cluster-Based Co-Saliency Detection

    Publication Year: 2013 , Page(s): 3766 - 3778
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5436 KB) |  | HTML iconHTML  

    Co-saliency is used to discover the common saliency on the multiple images, which is a relatively underexplored area. In this paper, we introduce a new cluster-based algorithm for co-saliency detection. Global correspondence between the multiple images is implicitly learned during the clustering process. Three visual attention cues: contrast, spatial, and corresponding, are devised to effectively ... View full abstract»

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  • Hierarchical Super-Resolution-Based Inpainting

    Publication Year: 2013 , Page(s): 3779 - 3790
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3073 KB) |  | HTML iconHTML  

    This paper introduces a novel framework for examplar-based inpainting. It consists in performing first the inpainting on a coarse version of the input image. A hierarchical super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of com... View full abstract»

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  • On the Method of Logarithmic Cumulants for Parametric Probability Density Function Estimation

    Publication Year: 2013 , Page(s): 3791 - 3806
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1195 KB) |  | HTML iconHTML  

    Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We de... View full abstract»

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  • Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition

    Publication Year: 2013 , Page(s): 3807 - 3817
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (681 KB) |  | HTML iconHTML  

    Manifold learning concerns the local manifold structure of high dimensional data, and many related algorithms are developed to improve image classification performance. None of them, however, consider both the relationships among pixels in images and the geometrical properties of various images during learning the reduced space. In this paper, we propose a linear approach, called two-dimensional m... View full abstract»

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  • Luma-Chroma Space Filter Design for Subpixel-Based Monochrome Image Downsampling

    Publication Year: 2013 , Page(s): 3818 - 3829
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2590 KB) |  | HTML iconHTML  

    In general, subpixel-based downsampling can achieve higher apparent resolution of the down-sampled images on LCD or OLED displays than pixel-based downsampling. With the frequency domain analysis of subpixel-based downsampling, we discover special characteristics of the luma-chroma color transform choice for monochrome images. With these, we model the anti-aliasing filter design for subpixel-based... View full abstract»

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  • Image Size Invariant Visual Cryptography for General Access Structures Subject to Display Quality Constraints

    Publication Year: 2013 , Page(s): 3830 - 3841
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (592 KB) |  | HTML iconHTML  

    Conventional visual cryptography (VC) suffers from a pixel-expansion problem, or an uncontrollable display quality problem for recovered images, and lacks a general approach to construct visual secret sharing schemes for general access structures. We propose a general and systematic approach to address these issues without sophisticated codebook design. This approach can be used for binary secret ... View full abstract»

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  • An Efficient Algorithm for Multiphase Image Segmentation With Intensity Bias Correction

    Publication Year: 2013 , Page(s): 3842 - 3851
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1442 KB) |  | HTML iconHTML  

    This paper presents a variational model for simultaneous multiphase segmentation and intensity bias estimation for images corrupted by strong noise and intensity inhomogeneity. Since the pixel intensities are not reliable samples for region statistics due to the presence of noise and intensity bias, we use local information based on the joint density within image patches to perform image partition... View full abstract»

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  • Monocular Human Motion Tracking by Using DE-MC Particle Filter

    Publication Year: 2013 , Page(s): 3852 - 3865
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2323 KB) |  | HTML iconHTML  

    Tracking human motion from monocular video sequences has attracted significantly increased interests in recent years. A key to accomplishing this task is to efficiently explore a high-dimensional state space. However, the traditional particle filter method and many of its variants have not been able to meet expectations as they lack a strategy to do efficiently sampling or stochastic search. We pr... View full abstract»

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  • Sparse Texture Active Contour

    Publication Year: 2013 , Page(s): 3866 - 3878
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5964 KB) |  | HTML iconHTML  

    In image segmentation, we are often interested in using certain quantities to characterize the object, and perform the classification based on criteria such as mean intensity, gradient magnitude, and responses to certain predefined filters. Unfortunately, in many cases such quantities are not adequate to model complex textured objects. Along a different line of research, the sparse characteristic ... View full abstract»

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  • Video Texture Synthesis With Multi-Frame LBP-TOP and Diffeomorphic Growth Model

    Publication Year: 2013 , Page(s): 3879 - 3891
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1787 KB) |  | HTML iconHTML  

    Video texture synthesis is the process of providing a continuous and infinitely varying stream of frames, which plays an important role in computer vision and graphics. However, it still remains a challenging problem to generate high-quality synthesis results. Considering the two key factors that affect the synthesis performance, frame representation and blending artifacts, we improve the synthesi... View full abstract»

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  • A Modified Model of the Just Noticeable Depth Difference and Its Application to Depth Sensation Enhancement

    Publication Year: 2013 , Page(s): 3892 - 3903
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1939 KB) |  | HTML iconHTML  

    The just noticeable depth difference (JNDD) describes the threshold of human perception of the difference in the depth. In flat-panel-based three-dimensional (3-D) displays, the JNDD is typically measured by changing the depth difference between displayed image objects until the difference is perceivable. However, not only the depth, but also the perceived size changes when the depth difference in... View full abstract»

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  • Sparse tensor discriminant analysis

    Publication Year: 2013 , Page(s): 3904 - 3915
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (744 KB) |  | HTML iconHTML  

    The classical linear discriminant analysis has undergone great development and has recently been extended to different cases. In this paper, a novel discriminant subspace learning method called sparse tensor discriminant analysis (STDA) is proposed, which further extends the recently presented multilinear discriminant analysis to a sparse case. Through introducing the L1 and L... View full abstract»

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  • Intra Prediction Based on Markov Process Modeling of Images

    Publication Year: 2013 , Page(s): 3916 - 3925
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (551 KB) |  | HTML iconHTML  

    In recent video coding standards, intraprediction of a block of pixels is performed by copying neighbor pixels of the block along an angular direction inside the block. Each block pixel is predicted from only one or few directionally aligned neighbor pixels of the block. Although this is a computationally efficient approach, it ignores potentially useful correlation of other neighbor pixels of the... View full abstract»

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  • Spline-Based Deforming Ellipsoids for Interactive 3D Bioimage Segmentation

    Publication Year: 2013 , Page(s): 3926 - 3940
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1802 KB) |  | HTML iconHTML  

    We present a new fast active-contour model (a.k.a. snake) for image segmentation in 3D microscopy. We introduce a parametric design that relies on exponential B-spline bases and allows us to build snakes that are able to reproduce ellipsoids. We design our bases to have the shortest-possible support, subject to some constraints. Thus, computational efficiency is maximized. The proposed 3D snake ca... View full abstract»

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  • Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization

    Publication Year: 2013 , Page(s): 3941 - 3949
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (319 KB) |  | HTML iconHTML  

    Consider the problem of reconstructing a multidimensional signal from an underdetermined set of measurements, as in the setting of compressed sensing. Without any additional assumptions, this problem is ill-posed. However, for signals such as natural images or movies, the minimal total variation estimate consistent with the measurements often produces a good approximation to the underlying signal,... View full abstract»

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  • Bandlimited Reconstruction of Multidimensional Images From Irregular Samples

    Publication Year: 2013 , Page(s): 3950 - 3960
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2001 KB) |  | HTML iconHTML  

    We examine different sampling lattices and their respective bandlimited spaces for reconstruction of irregularly sampled multidimensional images. Considering an irregularly sampled dataset, we demonstrate that the non-tensor-product bandlimited approximations corresponding to the body-centered cubic and face-centered cubic lattices provide a more accurate reconstruction than the tensor-product ban... View full abstract»

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  • Incorporating Anatomical Side Information Into PET Reconstruction Using Nonlocal Regularization

    Publication Year: 2013 , Page(s): 3961 - 3973
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2522 KB) |  | HTML iconHTML  

    With the introduction of combined positron emission tomography (PET)/computed tomography (CT) or PET/magnetic resonance imaging (MRI) scanners, there is an increasing emphasis on reconstructing PET images with the aid of the anatomical side information obtained from X-ray CT or MRI scanners. In this paper, we propose a new approach to incorporating prior anatomical information into PET reconstruct... View full abstract»

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  • DCT/DST-Based Transform Coding for Intra Prediction in Image/Video Coding

    Publication Year: 2013 , Page(s): 3974 - 3981
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (426 KB) |  | HTML iconHTML  

    In this paper, we present a DCT/DST based transform scheme that applies either the conventional DCT or type-7 DST for all the video-coding intra-prediction modes: vertical, horizontal, and oblique. Our approach is applicable to any block-based intra prediction scheme in a codec that employs transforms along the horizontal and vertical direction separably. Previously, Han, Saxena, and Rose showed t... View full abstract»

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Aims & Scope

IEEE Transactions on Image Processing focuses on signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing.

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Meet Our Editors

Editor-in-Chief
Scott Acton
University of Virginia
Charlottesville, VA, USA
E-mail: acton@virginia.edu 
Phone: +1 434-982-2003