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Image Processing, IEEE Transactions on

Issue 8 • Date Aug 1995

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Displaying Results 1 - 17 of 17
  • Region-of-interest tomography using exponential radial sampling

    Publication Year: 1995 , Page(s): 1120 - 1127
    Cited by:  Papers (8)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (668 KB)  

    The authors combine several ideas, including nonuniform sampling and circular harmonic expansions, into a new procedure for reconstructing a small region of interest (ROI) of an image from a set of its projections that are densely sampled in the ROI and coarsely sampled outside the ROI. Specifically, the radial sampling density of both the projections and the reconstructed image decreases exponentially with increasing distance from the ROI. The problem and data are reminiscent of the recently formulated local tomography problem; however, the authors' algorithm reconstructs the ROI of the image itself, not the filtered version of it obtained using local tomography. The new algorithm has the added advantages of speed (it can be implemented entirely using the FFT) and parallelizability (each image harmonic is computed independently). Numerical examples compare the new algorithm to filtered backprojection View full abstract»

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  • Multiresolution multiresource progressive image transmission

    Publication Year: 1995 , Page(s): 1128 - 1140
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1424 KB)  

    This paper presents a new progressive image transmission (PIT) design algorithm in which the resolution and resources (rate or distortion and storage size) at each transmission stage are allowed to be prespecified. This algorithm uses the wavelet transform and tree-structured vector quantizer (TSVQ) techniques. The wavelet transform is used to obtain a pyramid structure representation of an image. The vector quantizer technique is used to design a TSVQ for each subimage so that all the subimages that constitute the image at the current stage can be successively refined according to the resources available at that stage. The resources assigned to each subimage for the successive refinement is determined to optimize the performance at the current stage under the resource constraints. Normally, the resource constraints at each stage are determined by the specification of the transmission time or distortion for image data and the storage complexity of the TSVQ. The resolution at each stage is determined/specified according to the application or as part of the design process to optimize the visual effect View full abstract»

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  • Wavelet filter evaluation for image compression

    Publication Year: 1995 , Page(s): 1053 - 1060
    Cited by:  Papers (196)  |  Patents (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (848 KB)  

    Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2L,2L). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design View full abstract»

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  • Combined techniques of singular value decomposition and vector quantization for image coding

    Publication Year: 1995 , Page(s): 1141 - 1146
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (572 KB)  

    The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding. Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described. Simulation results show that the proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity View full abstract»

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  • Improvement on image transform coding by reducing interblock correlation

    Publication Year: 1995 , Page(s): 1146 - 1150
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (732 KB)  

    We try to improve transform coding efficiency by alleviating the interblock correlation due to the small size of the block. The proposed method needs minor modification from conventional transform coding techniques such as JPEG, and reduces the information loss in the coding procedure for a given bit rate. Simulation results demonstrate that the method drastically diminishes the blocking effects and enhances the subjective visual quality compared with such existing algorithms as JPEG and LOT View full abstract»

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  • Permutation weighted order statistic filter lattices

    Publication Year: 1995 , Page(s): 1070 - 1083
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1180 KB)  

    We introduce and analyze a new class of nonlinear filters called permutation weighted order statistic (PWOS) filters. These filters extend the concept of weighted order statistic (WOS) filters, in which filter weights associated with the input samples are used to replicate the corresponding samples, and an order statistic is chosen as the filter output. PWOS filters replicate each input sample according to weights determined by the temporal-order and rank-order of samples within a window. Hence, PWOS filters are in essence time-varying WOS filters. By varying the amount of temporal-rank order information used in selecting the output for a given observation window size, we obtain a wide range of filters that are shown to comprise a complete lattice structure. At the simplest level in the lattice, PWOS filters reduce to the well-known WOS filter, but for higher levels in the lattice, the obtained selection filters can model complex nonlinear systems and signal distortions. It is shown that PWOS filters are realizable by a N! piecewise linear threshold logic gate where the coefficients within each partition can be easily optimized using stack filter theory. Simulations are included to show the advantages of PWOS filters for the processing of image and video signals View full abstract»

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  • Regularized constrained total least squares image restoration

    Publication Year: 1995 , Page(s): 1096 - 1108
    Cited by:  Papers (47)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (956 KB)  

    In this paper, the problem of restoring an image distorted by a linear space-invariant (LSI) point-spread function (PSF) that is not exactly known is formulated as the solution of a perturbed set of linear equations. The regularized constrained total least-squares (RCTLS) method is used to solve this set of equations. Using the diagonalization properties of the discrete Fourier transform (DFT) for circulant matrices, the RCTLS estimate is computed in the DFT domain. This significantly reduces the computational cost of this approach and makes its implementation possible even for large images. An error analysis of the RCTLS estimate, based on the mean-squared-error (MSE) criterion, is performed to verify its superiority over the constrained total least-squares (CTLS) estimate. Numerical experiments for different errors in the PSF are performed to test the RCTLS estimator. Objective and visual comparisons are presented with the linear minimum mean-squared-error (LMMSE) and the regularized least-squares (RLS) estimator. Our experiments show that the RCTLS estimator reduces significantly ringing artifacts around edges as compared to the two other approaches View full abstract»

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  • Low entropy image pyramids for efficient lossless coding

    Publication Year: 1995 , Page(s): 1150 - 1153
    Cited by:  Papers (8)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB)  

    An efficient image source coding technique gives good compression performance at low computational complexity. This research introduces an efficient coding technique, based on pyramid coding, that involves transforming an image into an equivalent lower entropy form prior to lossless coding. The proposed method is also a multiresolution technique that facilitates progressive image transmission View full abstract»

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  • Expectation-maximization algorithms, null spaces, and MAP image restoration

    Publication Year: 1995 , Page(s): 1084 - 1095
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1168 KB)  

    A computationally efficient, easily implementable algorithm for MAP restoration of images degraded by blur and additive correlated Gaussian noise using Gibbs prior density functions is derived. This algorithm is valid for a variety of complete data spaces. The constraints upon the complete data space arising from the Gaussian image formation model are analyzed and a motivation is provided for the choice of the complete data, based upon the ease of computation of the resulting EM algorithms. The overlooked role of the null space of the blur operator in image restoration is introduced. An examination of this role reveals an important drawback to the use of the simulated annealing algorithm in maximizing a specific class of functionals. An alternative iterative method for computing the nullspace component of a vector is given. The ability of a simple Gibbs prior density function to enable partial recovery of the component of an image within the nullspace of the blur operator is demonstrated View full abstract»

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  • Two-dimensional filter bank design for optimal reconstruction using limited subband information

    Publication Year: 1995 , Page(s): 1160 - 1165
    Cited by:  Papers (11)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (748 KB)  

    In this correspondence, we propose design techniques for analysis and synthesis filters of 2-D perfect reconstruction filter banks (PRFB's) that perform optimal reconstruction when a reduced number of subband signals is used. Based on the minimization of the squared error between the original signal and some low-resolution representation of it, the 2-D filters are optimally adjusted to the statistics of the input images so that most of the signal's energy is concentrated in the first few subband components. This property makes the optimal PRFB's efficient for image compression and pattern representations at lower resolutions for classification purposes. By extending recently introduced ideas from frequency domain principal component analysis to two dimensions, we present results for general 2-D discrete nonstationary and stationary second-order processes, showing that the optimal filters are nonseparable. Particular attention is paid to separable random fields, proving that only the first and last filters of the optimal PRFB are separable in this case. Simulation results that illustrate the theoretical achievements are presented View full abstract»

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  • A finite mixtures algorithm for finding proportions in SAR images

    Publication Year: 1995 , Page(s): 1182 - 1186
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (432 KB)  

    This correspondence describes an algorithm for estimating the proportions of classes in an SAR image by first assuming that an image consists of a mixture of a known number of different pixel types. A maximum likelihood estimate of the parameters of the resulting mixture distribution is then evaluated using the EM algorithm. An advantage of the finite mixtures approach is that the quantities of interest, the proportions, are directly estimated. The technique is applied to aircraft synthetic aperture radar (SAR) images of sea ice. In addition to finding the proportions of the classes, knowledge of the mixture components allows image displays tailored to a user's requirements View full abstract»

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  • Image coding using adaptive recursive interpolative DPCM

    Publication Year: 1995 , Page(s): 1061 - 1069
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (824 KB)  

    A predictive image coder having minimal decoder complexity is presented. The image coder utilizes recursive interpolative DPCM in conjunction with adaptive classification, entropy-constrained trellis coded quantization, and optimal rate allocation to obtain signal-to-noise ratios (SNRs) in the range of those provided by the most advanced transform coders View full abstract»

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  • Flat zones filtering, connected operators, and filters by reconstruction

    Publication Year: 1995 , Page(s): 1153 - 1160
    Cited by:  Papers (114)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (852 KB)  

    This correspondence deals with the notion of connected operators. Starting from the definition for operator acting on sets, it is shown how to extend it to operators acting on function. Typically, a connected operator acting on a function is a transformation that enlarges the partition of the space created by the flat zones of the functions. It is shown that from any connected operator acting on sets, one can construct a connected operator for functions (however, it is not the unique way of generating connected operators for functions). Moreover, the concept of pyramid is introduced in a formal way. It is shown that, if a pyramid is based on connected operators, the flat zones of the functions increase with the level of the pyramid. In other words, the flat zones are nested. Filters by reconstruction are defined and their main properties are presented. Finally, some examples of application of connected operators and use of flat zones are described View full abstract»

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  • Stochastic modeling and estimation of multispectral image data

    Publication Year: 1995 , Page(s): 1109 - 1119
    Cited by:  Papers (5)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1328 KB)  

    Multispectral images consist of multiple channels, each containing data acquired from a different band within the frequency spectrum. Since most objects emit or reflect energy over a large spectral bandwidth, there usually exists a significant correlation between channels. Due to often harsh imaging environments, the acquired data may be degraded by both blur and noise. Simply applying a monochromatic restoration algorithm to each frequency band ignores the cross-channel correlation present within a multispectral image. A Gibbs prior is proposed for multispectral data modeled as a Markov random field, containing both spatial and spectral cliques. Spatial components of the model use a nonlinear operator to preserve discontinuities within each frequency band, while spectral components incorporate nonstationary cross-channel correlations. The multispectral model is used in a Bayesian algorithm for the restoration of color images, in which the resulting nonlinear estimates are shown to be quantitatively and visually superior to linear estimates generated by multichannel Wiener and least squares restoration View full abstract»

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  • Image restoration using the W-slice method

    Publication Year: 1995 , Page(s): 1174 - 1181
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (812 KB)  

    We propose the use of higher order statistics (HOS)-based methods to address the problem of image restoration. The restoration strategy is based on the fact that the phase information of the original image and its HOS are not distorted by some types of blurring. The difficulties associated with the combination of 2-D signals and their HOS are reduced by means of the Radon transform. Two methods that apply the weight-slice algorithm over the projections are developed. Simulation results illustrate the performance of the proposed methods View full abstract»

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  • A fuzzy operator for the enhancement of blurred and noisy images

    Publication Year: 1995 , Page(s): 1169 - 1174
    Cited by:  Papers (26)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB)  

    Rule-based fuzzy operators are a novel class of operators specifically designed in order to apply the principles of approximate reasoning to digital image processing. This paper shows how a fuzzy operator that is able to perform detail sharpening but is insensitive to noise can be designed. The results obtainable by the proposed technique in the enhancement of a real image are presented View full abstract»

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  • The relationship of the multi-shell to multistage and standard median filters

    Publication Year: 1995 , Page(s): 1165 - 1169
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (764 KB)  

    It is shown that for a particular window size, by changing gradually the minimum and maximum operators to the higher and lower order statistics of the shell, respectively, the multi-shell median filter will gradually turn from a multistage max/median filter into a 2-D standard median filter 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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Editor-in-Chief
Scott Acton
University of Virginia
Charlottesville, VA, USA
E-mail: acton@virginia.edu 
Phone: +1 434-982-2003