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Image Processing, IEEE Transactions on

Issue 11 • Date Nov 1997

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Displaying Results 1 - 13 of 13
  • Comparison of different methods of classification in subband coding of images

    Page(s): 1473 - 1486
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB)  

    This paper investigates various classification techniques, applied to subband coding of images, as a way of exploiting the nonstationary nature of image subbands. The advantages of subband classification are characterized in a rate-distortion framework in terms of “classification gain” and overall “subband classification gain.” Two algorithms, maximum classification gain and equal mean-normalized standard deviation classification, which allow unequal number of blocks in each class, are presented. The dependence between the classification maps from different subbands is exploited either directly while encoding the classification maps or indirectly by constraining the classification maps. The trade-off between the classification gain and the amount of side information is explored. Coding results for a subband image coder based on classification are presented. The simulation results demonstrate the value of classification in subband coding View full abstract»

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  • Local cosine bases in two dimensions

    Page(s): 1580 - 1583
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB)  

    We construct two-dimensional (2-D) local cosine bases in discrete time. Solutions are offered both for rectangular and nonrectangular lattices. In the case of nonrectangular lattices, the problem is solved by mapping it into a one-dimensional (1-D) equivalent problem View full abstract»

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  • Automatic watershed segmentation of randomly textured color images

    Page(s): 1530 - 1544
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB)  

    A new method is proposed for processing randomly textured color images. The method is based on a bottom-up segmentation algorithm that takes into consideration both color and texture properties of the image. An LUV gradient is introduced, which provides both a color similarity measure and a basis for applying the watershed transform. The patches of watershed mosaic are merged according to their color contrast until a termination criterion is met. This criterion is based on the topology of the typical processed image. The resulting algorithm does not require any additional information, be it various thresholds, marker extraction rules, and suchlike, thus being suitable for automatic processing of color images. The algorithm is demonstrated within the framework of the problem of automatic granite inspection. The segmentation procedure has been found to be very robust, producing good results not only on granite images, but on the wide range of other noisy color images as well, subject to the termination criterion View full abstract»

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  • Motion estimation based on global and local uncompensability analysis

    Page(s): 1584 - 1587
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (116 KB)  

    This correspondence reports our study of a novel motion estimation technique for image sequence coding by exploiting the uncompensable characteristic of the motion field. Preliminary results indicate that this technique not only reduces the estimation burden drastically but also improves the subjective picture quality and signal-to-noise ratio (SNR) View full abstract»

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  • Multispectral code excited linear prediction coding and its application in magnetic resonance images

    Page(s): 1555 - 1566
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (372 KB)  

    This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256×256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously View full abstract»

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  • Airborne synthetic aperture acoustic imaging

    Page(s): 1545 - 1554
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (648 KB)  

    This paper presents a system model and inversion for airborne synthetic aperture acoustic (SAA) imaging. The system model accurately represents the intercation of the acoustic source and the target region at near range values. Moreover, the model incorporates the fact that the relative speed of the vehicle's (transmitter/receiver) with respect to the target region is comparable to the acoustic wave propagation speed. The inversion utilizes the principle of spectral decomposition of spherical phase functions to develop a wavefront reconstruction method from SAA data. Processing issues and selection of appropriate acoustic FM-CW sources are discussed. Results are provided that exhibit the superior accuracy of the proposed SAA system model and inversion over their synthetic aperture radar (SAR) counterpart in which the vehicle's speed is assumed to be much smaller than the wave propagation speed View full abstract»

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  • Motion field modeling for video sequences

    Page(s): 1503 - 1516
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB)  

    We propose a model for the interframe correspondences existing between pixels of an image sequence. These correspondences form the elements of a field called the motion field. In our model, spatial neighborhoods of motion elements are related based on a generalization of autoregressive (AR) modeling of the time-series. We also propose a joint spatio-temporal model by including spatial neighborhoods of pixel intensities in the motion model. A fundamental difference of our approach with most previous approaches to modeling motion is in basing our model on concepts from statistical signal processing. The developments in this paper give rise to the promise of extending well-understood tools of signal processing (e.g., filtering) to the analysis and processing of motion fields. Simulation results presented show the performance of our models in interframe prediction; specifically, on average the motion model performs 29% better in terms of the mean squared error energy over a commonly used pel-recursive approach. The spatio-temporal model improves the prediction efficiencies by 8% over the motion model. Our model can also be used to obtain estimates of the optical flow field as the simulations demonstrate View full abstract»

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  • Entropy-constrained halftoning using multipath tree coding

    Page(s): 1567 - 1579
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1624 KB)  

    We suggest an optimization-based method for halftoning that involves looking ahead before a decision for each binary output pixel is made. We first define a mixture distortion criterion that is a combination of a frequency-weighted mean square error (MSE) and a measure depending on the distances between minority pixels in the halftone. A tree-coding approach with the ML-algorithm is used for minimizing the distortion criterion to generate a halftone. While this approach generates halftones of high quality, these halftones are not very amenable to lossless compression. We introduce an entropy constraint into the cost function of the tree-coding algorithm that optimally trades off between image quality and compression performance in the output halftones View full abstract»

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  • A fast motion estimation algorithm based on the block sum pyramid

    Page(s): 1587 - 1591
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (140 KB)  

    In this correspondence, a fast approach to motion estimation is presented. The algorithm uses the block sum pyramid to eliminate unnecessary search positions. It first constructs the sum pyramid structure of a block. Successive elimination is then performed hierarchically from the top level to the bottom level of the pyramid. Many search positions can be skipped from being considered as the best motion vector and, thus, the search complexity can be reduced. The algorithm can achieve the same estimation accuracy as the full search block matching algorithm with much less computation time View full abstract»

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  • Motion segmentation by multistage affine classification

    Page(s): 1591 - 1594
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB)  

    We present a multistage affine motion segmentation method that combines the benefits of the dominant motion and block-based affine modeling approaches. In particular, we propose two key modifications to a recent motion segmentation algorithm developed by Wang and Adelson (1994). 1) The adaptive k-means clustering step is replaced by a merging step, whereby the affine parameters of a block which has the smallest representation error, rather than the respective cluster center, is used to represent each layer; and 2) we implement it in multiple stages, where pixels belonging to a single motion model are labeled at each stage. Performance improvement due to the proposed modifications is demonstrated on real video frames View full abstract»

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  • On the detection of edges in vector images

    Page(s): 1595 - 1601
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB)  

    A novel method for edge detection in vector images is proposed that does not require any prior knowledge of the imaged scenes. In the derivation, it is assumed that the observed vector images are realizations of spatially quasistationary processes, and that the vector observations are generated by parametric probability distribution functions of known form whose parameters are in general unknown. The method detects and estimates the edge locations using a criterion derived by Bayesian theory. It chooses the number of edges and their locations according to the maximum a posteriori probability (MAP) principle. We provide results that demonstrate its performance on synthesized and real images View full abstract»

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  • An overlapping tree approach to multiscale stochastic modeling and estimation

    Page(s): 1517 - 1529
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (984 KB)  

    Recently, a class of multiscale stochastic models has been introduced in which random processes and fields are described by scale-recursive dynamic trees. A major advantage of this framework is that it leads to an extremely efficient, statistically optimal algorithm for least-squares estimation. In certain applications, however, estimates based on the types of multiscale models previously proposed may not be adequate, as they have tended to exhibit a visually distracting blockiness. We eliminate this blockiness by discarding the standard assumption that distinct nodes on a given level of the multiscale process correspond to disjoint portions of the image domain; instead, we allow a correspondence to overlapping portions of the image domain. We use these so-called overlapping-tree models for both modeling and estimation. In particular, we develop an efficient multiscale algorithm for generating sample paths of a random field whose second-order statistics match a prespecified covariance structure, to any desired degree of fidelity. Furthermore, we demonstrate that under easily satisfied conditions, we can “lift” a random field estimation problem to one defined on an overlapped tree, resulting in an estimation algorithm that is computationally efficient, directly produces estimation error covariances, and eliminates blockiness in the reconstructed imagery without any sacrifice in the resolution of fine-scale detail View full abstract»

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  • A video compression scheme with optimal bit allocation among segmentation, motion, and residual error

    Page(s): 1487 - 1502
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (676 KB)  

    We present a theory for the optimal bit allocation among quadtree (QT) segmentation, displacement vector field (DVF), and displaced frame difference (DFD). The theory is applicable to variable block size motion-compensated video coders (VBSMCVC), where the variable block sizes are encoded using the QT structure, the DVF is encoded by first-order differential pulse code modulation (DPCM), the DFD is encoded by a block-based scheme, and an additive distortion measure is employed. We derive an optimal scanning path for a QT that is based on a Hilbert curve. We consider the case of a lossless VBSMCVC first, for which we develop the optimal bit allocation algorithm using dynamic programming (DP). We then consider a lossy VBSMCVC, for which we use Lagrangian relaxation, and show how an iterative scheme, which employs the DP-based solution, can be used to find the optimal solution. We finally present a VBSMCVC, which is based on the proposed theory, which employs a DCT-based DFD encoding scheme. We compare the proposed coder with H.263. The results show that it outperforms H.263 significantly in the rate distortion sense, as well as in the subjective sense 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