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IEEE Transactions on Image Processing

Issue 4 • Date April 2014

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Displaying Results 1 - 25 of 48
  • [Front cover]

    Publication Year: 2014, Page(s): C1
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  • IEEE Transactions on Image Processing publication information

    Publication Year: 2014, Page(s): C2
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  • Table of contents

    Publication Year: 2014, Page(s):1443 - 1444
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  • [Blank page]

    Publication Year: 2014, Page(s):1445 - 1446
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  • Table of contents

    Publication Year: 2014, Page(s):1447 - 1449
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  • [Blank page]

    Publication Year: 2014, Page(s): B1450
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  • Lazy Random Walks for Superpixel Segmentation

    Publication Year: 2014, Page(s):1451 - 1462
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1663 KB) | HTML iconHTML

    We present a novel image superpixel segmentation approach using the proposed lazy random walk (LRW) algorithm in this paper. Our method begins with initializing the seed positions and runs the LRW algorithm on the input image to obtain the probabilities of each pixel. Then, the boundaries of initial superpixels are obtained according to the probabilities and the commute time. The initial superpixe... View full abstract»

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  • A Unified Data Embedding and Scrambling Method

    Publication Year: 2014, Page(s):1463 - 1475
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5830 KB) | HTML iconHTML

    Conventionally, data embedding techniques aim at maintaining high-output image quality so that the difference between the original and the embedded images is imperceptible to the naked eye. Recently, as a new trend, some researchers exploited reversible data embedding techniques to deliberately degrade image quality to a desirable level of distortion. In this paper, a unified data embedding-scramb... View full abstract»

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  • Saliency Prediction on Stereoscopic Videos

    Publication Year: 2014, Page(s):1476 - 1490
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6305 KB) | HTML iconHTML

    We describe a new 3D saliency prediction model that accounts for diverse low-level luminance, chrominance, motion, and depth attributes of 3D videos as well as high-level classifications of scenes by type. The model also accounts for perceptual factors, such as the nonuniform resolution of the human eye, stereoscopic limits imposed by Panum's fusional area, and the predicted degree of (dis) comfor... View full abstract»

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  • Progressive Image Denoising Through Hybrid Graph Laplacian Regularization: A Unified Framework

    Publication Year: 2014, Page(s):1491 - 1503
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (8268 KB) | HTML iconHTML

    Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse t... View full abstract»

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  • Analyzing Training Information From Random Forests for Improved Image Segmentation

    Publication Year: 2014, Page(s):1504 - 1512
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4844 KB) | HTML iconHTML

    Labeled training data are used for challenging medical image segmentation problems to learn different characteristics of the relevant domain. In this paper, we examine random forest (RF) classifiers, their learned knowledge during training and ways to exploit it for improved image segmentation. Apart from learning discriminative features, RFs also quantify their importance in classification. Featu... View full abstract»

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  • Image Classification Using Multiscale Information Fusion Based on Saliency Driven Nonlinear Diffusion Filtering

    Publication Year: 2014, Page(s):1513 - 1526
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2504 KB) | HTML iconHTML

    In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the i... View full abstract»

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  • Quality Assessment of Stereoscopic 3D Image Compression by Binocular Integration Behaviors

    Publication Year: 2014, Page(s):1527 - 1542
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3509 KB) | HTML iconHTML Multimedia Media

    The objective approaches of 3D image quality assessment play a key role for the development of compression standards and various 3D multimedia applications. The quality assessment of 3D images faces more new challenges, such as asymmetric stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. In addition, the widely used 2D image quality metrics (e.g., PSNR and... View full abstract»

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  • Parsimonious Path Openings and Closings

    Publication Year: 2014, Page(s):1543 - 1555
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3482 KB) | HTML iconHTML

    Path openings and closings are morphological tools used to preserve long, thin, and tortuous structures in gray level images. They explore all paths from a defined class, and filter them with a length criterion. However, most paths are redundant, making the process generally slow. Parsimonious path openings and closings are introduced in this paper to solve this problem. These operators only consi... View full abstract»

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  • Data-Driven Spatially-Adaptive Metric Adjustment for Visual Tracking

    Publication Year: 2014, Page(s):1556 - 1568
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5204 KB) | HTML iconHTML

    Matching visual appearances of the target over consecutive video frames is a fundamental yet challenging task in visual tracking. Its performance largely depends on the distance metric that determines the quality of visual matching. Rather than using fixed and predefined metric, recent attempts of integrating metric learning-based trackers have shown more robust and promising results, as the learn... View full abstract»

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  • Evaluation of Color Spatio-Temporal Interest Points for Human Action Recognition

    Publication Year: 2014, Page(s):1569 - 1580
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1804 KB) | HTML iconHTML

    This paper considers the recognition of realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena, such as shadows and highlights. In addition, valuable information is neglected by dis... View full abstract»

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  • Analysis and Exploitation of Multipath Ghosts in Radar Target Image Classification

    Publication Year: 2014, Page(s):1581 - 1592
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1193 KB) | HTML iconHTML

    An analysis of the relationship between multipath ghosts and the direct target image for radar imaging is presented. A multipath point spread function (PSF) is defined that allows for specular reflections in the local environment and can allow the ghost images to be localized. Analysis of the multipath PSF shows that certain ghosts can only be focused for the far field synthetic aperture radar cas... View full abstract»

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  • Manifold Learning for Object Tracking With Multiple Nonlinear Models

    Publication Year: 2014, Page(s):1593 - 1605
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3855 KB) | HTML iconHTML

    This paper presents a novel manifold learning algorithm for high-dimensional data sets. The scope of the application focuses on the problem of motion tracking in video sequences. The framework presented is twofold. First, it is assumed that the samples are time ordered, providing valuable information that is not presented in the current methodologies. Second, the manifold topology comprises multip... View full abstract»

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  • Contextual Hashing for Large-Scale Image Search

    Publication Year: 2014, Page(s):1606 - 1614
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1682 KB) | HTML iconHTML

    With the explosive growth of the multimedia data on the Web, content-based image search has attracted considerable attentions in the multimedia and the computer vision community. The most popular approach is based on the bag-of-visual-words model with invariant local features. Since the spatial context information among local features is critical for visual content identification, many methods exp... View full abstract»

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  • Spatiotemporal Grid Flow for Video Retargeting

    Publication Year: 2014, Page(s):1615 - 1628
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3766 KB) | HTML iconHTML

    Video retargeting is a useful technique to adapt a video to a desired display resolution. It aims to preserve the information contained in the original video and the shapes of salient objects while maintaining the temporal coherence of contents in the video. Existing video retargeting schemes achieve temporal coherence via constraining each region/pixel to be deformed consistently with its corresp... View full abstract»

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  • Clustering-Based Discriminant Analysis for Eye Detection

    Publication Year: 2014, Page(s):1629 - 1638
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1594 KB) | HTML iconHTML

    This paper proposes three clustering-based discriminant analysis (CDA) models to address the problem that the Fisher linear discriminant may not be able to extract adequate features for satisfactory performance, especially for two class problems. The first CDA model, CDA-1, divides each class into a number of clusters by means of the k-means clustering technique. In this way, a new within-cluster ... View full abstract»

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  • Robust Superpixel Tracking

    Publication Year: 2014, Page(s):1639 - 1651
    Cited by:  Papers (20)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5750 KB) | HTML iconHTML

    While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large appearance change due to factors such as scale, motion, shape deformation, and occlusion. One of the main reasons is the lack of effective image representation schemes to account for appearance variation. Most of the trackers use high-level appe... View full abstract»

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  • Lossy Cutset Coding of Bilevel Images Based on Markov Random Fields

    Publication Year: 2014, Page(s):1652 - 1665
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (7486 KB) | HTML iconHTML

    An effective, low complexity method for lossy compression of scenic bilevel images, called lossy cutset coding, is proposed based on a Markov random field model. It operates by losslessly encoding pixels in a square grid of lines, which is a cutset with respect to a Markov random field model, and preserves key structural information, such as borders between black and white regions. Relying on the ... View full abstract»

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  • Characterness: An Indicator of Text in the Wild

    Publication Year: 2014, Page(s):1666 - 1677
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1891 KB) | HTML iconHTML

    Text in an image provides vital information for interpreting its contents, and text in a scene can aid a variety of tasks from navigation to obstacle avoidance and odometry. Despite its value, however, detecting general text in images remains a challenging research problem. Motivated by the need to consider the widely varying forms of natural text, we propose a bottom-up approach to the problem, w... View full abstract»

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  • Tensor-Based Formulation and Nuclear Norm Regularization for Multienergy Computed Tomography

    Publication Year: 2014, Page(s):1678 - 1693
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3887 KB) | HTML iconHTML

    The development of energy selective, photon counting X-ray detectors allows for a wide range of new possibilities in the area of computed tomographic image formation. Under the assumption of perfect energy resolution, here we propose a tensor-based iterative algorithm that simultaneously reconstructs the X-ray attenuation distribution for each energy. We use a multilinear image model rather than a... 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