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Image Processing, IEEE Transactions on

Issue 6 • Date June 2003

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Displaying Results 1 - 12 of 12
  • Data hiding in image and video .II. Designs and applications

    Publication Year: 2003 , Page(s): 696 - 705
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1477 KB)  

    For pt. I see ibid., vol.12, no.6, p.685-95 (2003). This paper applies the solutions to the fundamental issues addressed in Part I to specific design problems of embedding data in image and video. We apply multilevel embedding to allow the amount of embedded information that can be reliably extracted to be adaptive with respect to the actual noise conditions. When extending the multilevel embedding to video, we propose strategies for handling uneven embedding capacity from region to region within a frame as well as from frame to frame. We also embed control information to facilitate the accurate extraction of the user data payload and to combat such distortions as frame jitter. The proposed algorithm can be used for a variety of applications such as copy control, access control, robust annotation, and content-based authentication. View full abstract»

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  • Multiscale gradient watersheds of color images

    Publication Year: 2003 , Page(s): 617 - 626
    Cited by:  Papers (20)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (873 KB)  

    We present a new framework for the hierarchical segmentation of color images. The proposed scheme comprises a nonlinear scale-space with vector-valued gradient watersheds. Our aim is to produce a meaningful hierarchy among the objects in the image using three image components of distinct perceptual significance for a human observer, namely strong edges, smooth segments and detailed segments. The scale-space is based on a vector-valued diffusion that uses the Additive Operator Splitting numerical scheme. Furthermore, we introduce the principle of the dynamics of contours in scale-space that combines scale and contrast information. The performance of the proposed segmentation scheme is presented via experimental results obtained with a wide range of images including natural and artificial scenes. View full abstract»

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  • Visualization of high dynamic range images

    Publication Year: 2003 , Page(s): 639 - 647
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1112 KB)  

    A novel paradigm for information visualization in high dynamic range images is presented in this paper. These images, real or synthetic, have luminance with typical ranges many orders of magnitude higher than that of standard output/viewing devices, thereby requiring some processing for their visualization. In contrast with existent approaches, which compute a single image with reduced range, close in a given sense to the original data, we propose to look for a representative set of images. The goal is then to produce a minimal set of images capturing the information all over the high dynamic range data, while at the same time preserving a natural appearance for each one of the images in the set. A specific algorithm that achieves this goal is presented and tested on natural and synthetic data. View full abstract»

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  • An orthogonal wavelet representation of multivalued images

    Publication Year: 2003 , Page(s): 718 - 725
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (639 KB) |  | HTML iconHTML  

    A new orthogonal wavelet representation of multivalued images is presented. The idea for this representation is based on the concept of maximal gradient of multivalued images. This concept is generalized from gradients toward linear vector operators in the image plane with equal components along rows and columns. Using this generalization, the pyramidal dyadic wavelet transform algorithm using quadrature mirror filters is modified to be applied to multivalued images. This results in a representation of a single image, containing multiscale detail information from all component images involved. This representation leads to multiple applications ranging from multispectral image fusion to color and multivalued image enhancement, denoising and segmentation. In this paper, the representation is applied for fusion of images. More in particular, we introduce a scheme to merge high spatial resolution greylevel images with low spatial resolution multivalued images to improve spatial resolution of the latter while preserving spectral resolution. Two applications are studied: demosaicing of color images and merging of multispectral remote sensing images. View full abstract»

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  • Data hiding in image and video .I. Fundamental issues and solutions

    Publication Year: 2003 , Page(s): 685 - 695
    Cited by:  Papers (52)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (661 KB)  

    We address a number of fundamental issues of data hiding in image and video and propose general solutions to them. We begin with a review of two major types of embedding, based on which we propose a new multilevel embedding framework to allow the amount of extractable data to be adaptive according to the actual noise condition. We then study the issues of hiding multiple bits through a comparison of various modulation and multiplexing techniques. Finally, the nonstationary nature of visual signals leads to highly uneven distribution of embedding capacity and causes difficulty in data hiding. We propose an adaptive solution switching between using constant embedding rate with shuffling and using variable embedding rate with embedded control bits. We verify the effectiveness of our proposed solutions through analysis and simulation. View full abstract»

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  • Gray and color image contrast enhancement by the curvelet transform

    Publication Year: 2003 , Page(s): 706 - 717
    Cited by:  Papers (144)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1713 KB) |  | HTML iconHTML  

    We present a new method for contrast enhancement based on the curvelet transform. The curvelet transform represents edges better than wavelets, and is therefore well-suited for multiscale edge enhancement. We compare this approach with enhancement based on the wavelet transform, and the multiscale retinex. In a range of examples, we use edge detection and segmentation, among other processing applications, to provide for quantitative comparative evaluation. Our findings are that curvelet based enhancement out-performs other enhancement methods on noisy images, but on noiseless or near noiseless images curvelet based enhancement is not remarkably better than wavelet based enhancement. View full abstract»

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  • Texture classification using spectral histograms

    Publication Year: 2003 , Page(s): 661 - 670
    Cited by:  Papers (55)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1086 KB) |  | HTML iconHTML  

    Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicitly the local structure of images through the filtering stage and the global appearance through the histogram stage. The distance between two spectral histograms is measured using χ2-statistic. The spectral histogram with the associated distance measure exhibits several properties that are necessary for texture classification. A filter selection algorithm is proposed to maximize classification performance of a given dataset. Our classification experiments using natural texture images reveal that the spectral histogram representation provides a robust feature statistic for textures and generalizes well. Comparisons show that our method produces a marked improvement in classification performance. Finally we point out the relationships between existing texture features and the spectral histogram, suggesting that the latter may provide a unified texture feature. View full abstract»

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  • Object segmentation and labeling by learning from examples

    Publication Year: 2003 , Page(s): 627 - 638
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2045 KB)  

    We propose a system that employs low-level image segmentation followed by color and two-dimensional (2-D) shape matching to automatically group those low-level segments into objects based on their similarity to a set of example object templates presented by the user. A hierarchical content tree data structure is used for each database image to store matching combinations of low-level regions as objects. The system automatically initializes the content tree with only "elementary nodes" representing homogeneous low-level regions. The "learning" phase refers to labeling of combinations of low-level regions that have resulted in successful color and/or 2-D shape matches with the example template(s). These combinations are labeled as "object nodes" in the hierarchical content tree. Once learning is performed, the speed of second-time retrieval of learned objects in the database increases significantly. The learning step can be performed off-line provided that example objects are given in the form of user interest profiles. Experimental results are presented to demonstrate the effectiveness of the proposed system with hierarchical content tree representation and learning by color and 2-D shape matching on collections of car and face images. View full abstract»

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  • A new predictive search area approach for fast block motion estimation

    Publication Year: 2003 , Page(s): 648 - 652
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (382 KB) |  | HTML iconHTML  

    According to the observation on the distribution of motion differentials among the motion vector of any block and those of its four neighboring blocks from six real video sequences, this paper presents a new predictive search area approach for fast block motion estimation. Employing our proposed simple predictive search area approach into the full search (FS) algorithm, our improved FS algorithm leads to 93.83% average execution-time improvement ratio, but only has a small estimation accuracy degradation. We also investigate the advantages of computation and estimation accuracy of our improved FS algorithm when compared to the edge-based search algorithm of Chan and Siu (see IEEE Trans. Image Processing, vol.10, p.1223-1238, Aug. 2001); experimental results reveal that our improved FS algorithm has 74.33% average execution-time improvement ratio and has a higher estimation accuracy. Finally, we further compare the performance among our improved FS algorithm, the three-step search algorithm, and the block-based gradient descent search algorithm. View full abstract»

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  • Multiresolution maximum intensity volume rendering by morphological adjunction pyramids

    Publication Year: 2003 , Page(s): 653 - 660
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (511 KB) |  | HTML iconHTML  

    We describe a multiresolution extension to maximum intensity projection (MIP) volume rendering, allowing progressive refinement and perfect reconstruction. The method makes use of morphological adjunction pyramids. The pyramidal analysis and synthesis operators are composed of morphological 3-D erosion and dilation, combined with dyadic downsampling for analysis and dyadic upsampling for synthesis. In this case the MIP operator can be interchanged with the synthesis operator. This fact is the key to an efficient multiresolution MIP algorithm, because it allows the computation of the maxima along the line of sight on a coarse level, before applying a two-dimensional synthesis operator to perform reconstruction of the projection image to a finer level. For interpolation and resampling of volume data, which is required to deal with arbitrary view directions, morphological sampling is used, an interpolation method well adapted to the nonlinear character of MIP. The structure of the resulting multiresolution rendering algorithm is very similar to wavelet splatting, the main differences being that (i) linear summation of voxel values is replaced by maximum computation, and (ii) linear wavelet filters are replaced by nonlinear morphological filters. View full abstract»

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  • Fast image transforms using diophantine methods

    Publication Year: 2003 , Page(s): 678 - 684
    Cited by:  Papers (3)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (610 KB)  

    Many image transformations in computer vision and graphics involve a pipeline when an initial integer image is processed with floating point computations for purposes of symbolic information. Traditionally, in the interests of time, the floating point computation is approximated by integer computations where the integerization process requires a guess of an integer. Examples of this phenomenon include the discretization interval of ρ and θ in the accumulator array in classical Hough transform, and in geometric manipulation of images (e.g., rotation, where a new grid is overlaid on the image). The result of incorrect discretization is a poor quality visual image, or worse, hampers measurements of critical parameters such as density or length in high fidelity machine vision. Correction techniques include, at best, anti-aliasing methods, or more commonly, a "kludge" to cleanup. In this paper, we present a method that uses the theory of basis reduction in Diophantine approximations; the method outperforms prior integer based computation without sacrificing accuracy (subject to machine epsilon). View full abstract»

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  • High-resolution reconstruction of sparse data from dense low-resolution spatio-temporal data

    Publication Year: 2003 , Page(s): 671 - 677
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (618 KB) |  | HTML iconHTML  

    A novel approach for reconstruction of sparse high-resolution data from lower-resolution dense spatio-temporal data is introduced. The basic idea is to compute the dense feature velocities from lower-resolution data and project them to the corresponding high-resolution data for computing the missing data. In this context, the basic flow equation is solved for intensity, as opposed to feature velocities at high resolution. Although the proposed technique is generic, we have applied our approach to sea surface temperature (SST) data at 18 km (low-resolution dense data) for computing the feature velocities and at 4 km (high-resolution sparse data) for interpolating the missing data. At low resolution, computation of the flow field is regularized and uses the incompressibility constraints for tracking fluid motion. At high resolution, computation of the intensity is regularized for continuity across multiple frames. 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