Super-resolution image reconstruction produces a high-resolution image or high- resolution image sequences from a set of shifted, blurred, and decimated versions thereof, and has been proven to be extremely useful in ...
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ISBN:
(纸本)9780819469502
Super-resolution image reconstruction produces a high-resolution image or high- resolution image sequences from a set of shifted, blurred, and decimated versions thereof, and has been proven to be extremely useful in early vision, video surveillance, and other applications. However, as magnification increases, previously published techniques get worse either in computational complexity or ringing artifacts. In this paper, a fast approach is proposed to reduce both the ringing artifacts and the computational complexity. Experiment results demonstrate that the new approach is more efficient and can provide much better reconstruction quality in comparison with normal super-resolution algorithms.
This paper proposes a difference-templates based target tracking method (DTBTTM) with the originality of constructing a collection of difference templates that represent the varying characteristics of target region, s...
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ISBN:
(纸本)9780819469502
This paper proposes a difference-templates based target tracking method (DTBTTM) with the originality of constructing a collection of difference templates that represent the varying characteristics of target region, such as translation, scale, and illumination. DTBTTM method uses the linear combination of such difference templates to represent the variation of target region, and computes coefficients with respect to the corresponding templates. The final target position and window size can be determined with these coefficients. DTBTTM method simply solves linear equations, and is quite different from correlation method in which 2-dimensional search is required to calculate similarity between pre-defined template and the region of interest. Experimental results show that the DTBTTM is highly adaptable to the variation of target region, and is robust to the variation of translation, scale, illumination, and even occlusion.
Finite ridgelet transform (FRIT) overcomes the weakness of wavelet transform representing in two or higher dimensions and FRIT can efficiently represent the singularity of linear in image. When FRIT is applied to imag...
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ISBN:
(纸本)9780819469502
Finite ridgelet transform (FRIT) overcomes the weakness of wavelet transform representing in two or higher dimensions and FRIT can efficiently represent the singularity of linear in image. When FRIT is applied to image fusion, the characters of original images can be effectively extracted and more important information is preserved. In this paper, we discussed the advantage of FRIT applying to the image fusion and the process of the fusion algorithm based on FRIT in details. Two sets of images are taken as experimental data, subjective and objective standard are used to evaluate the results. The experiment results show that the FRIT algorithm gets much better fusion results than wavelet, and image fusion algorithm based on FRIT is an effective and feasible algorithm.
In this paper, we discuss the image denoising model which DeVore et al. had established, in which both distance and smoothness can be measured by the objective function, and analysis the model for wavelet image denois...
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ISBN:
(纸本)9780819469502
In this paper, we discuss the image denoising model which DeVore et al. had established, in which both distance and smoothness can be measured by the objective function, and analysis the model for wavelet image denoising in the Besov spaces with p = q . In addition, we give the exact thresholds for the model, and prove that for 0 < p < 1 the effect of noise removal using our methods is in between hard wavelet shrinkage and soft wavelet shrinkage. For the case 0 < p < 1 and 1 < p < ∞, which refers to the problems on the convergence of the iteration of the equations and on the complexity of computation, we give the simplified algorithms. Comparing the threshold given by this paper with Lorenz threshold, we conclude that the former is more meticulous than the latter for the model.
It is difficult to get ideal effect that research on target enhancement and segmentation are developed by simply using features of edge, texture and gray in complex background. Studies on target enhancement and segmen...
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ISBN:
(纸本)9780819469502
It is difficult to get ideal effect that research on target enhancement and segmentation are developed by simply using features of edge, texture and gray in complex background. Studies on target enhancement and segmentation have always been the research focus for a long time. Considering known regular shape target in complex background, an approach of target enhancement and segment based on shape feature is proposed. According to analyze the shape of regular target such as line and arc, first, Top-hat is used to enhance target. Then, threshold segmentation method, thinning and deburring are following. Third, a new image is acquired by the Hough transform which can find points in edge image similar with target in shape and property. The very points would be reserved. Moreover, the new image acquired is the initial condition of reconstruction, the original image is limit condition, and target enhancement is achieved by grayscale morphological reconstruction. Finally, binaryzation processing of image was used to segment target. Experimental results demonstrate that the proposed algorithm has an encouraging performance.
A novel adaptive multi threshold image segmentation algorithm is proposed in this paper. This proposed segmentation algorithm has two unique characteristics: it fits the 1-D graylevel histogram of the image by potenti...
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ISBN:
(纸本)9780819469502
A novel adaptive multi threshold image segmentation algorithm is proposed in this paper. This proposed segmentation algorithm has two unique characteristics: it fits the 1-D graylevel histogram of the image by potential base function and thereby adaptively determines the classification number by potential function clustering;based on the graylevel co-occurrence matrix, it acquires the multi segmentation thresholds which makes the shape connectivity maximum according to the shape connectivity criterion. Both theoretical analysis and simulation results indicate that the performance of this new adaptive multi threshold segmentation algorithm is superior to those of the conventional threshold segmentation algorithms. And it has not only a low computing cost, but also shows quite good segmentation effect. Besides, it is insensitive to noises and interferences.
In order to conquer the drawback of over-smoothness in the MRF model, a kind of discontinuity-adaptive Gaussian Markov random field (DA-GMRF) model is defined, in which the edge information of image is used to constru...
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ISBN:
(纸本)9780819469502
In order to conquer the drawback of over-smoothness in the MRF model, a kind of discontinuity-adaptive Gaussian Markov random field (DA-GMRF) model is defined, in which the edge information of image is used to construct corresponding energy functions. After this a FLIR image segmentation method based on DA-GMRF model is proposed, which includes initialization and optimization of the label field. A multi-threshold image segmentation algorithm based on potential function of gray histogram is presented to initialize the label field. This algorithm can determine region number and multi-thresholds automatically. Metroplis Sampler algorithm is adopted to optimize the label field. Segmentation experiments on several images show that the algorithm proposed is effective.
Based on region-segmentation method and flame image edge detection operator, flame image pre-processing and edge detection can effectively improve flame image processing efficiency. Relatively effective flame image ed...
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ISBN:
(纸本)9780819469502
Based on region-segmentation method and flame image edge detection operator, flame image pre-processing and edge detection can effectively improve flame image processing efficiency. Relatively effective flame image edge detection operator is proposed in this paper. It provides basis for further flame parameters extraction.
In this paper, a SGNN (Self-Generating Neural Network)-based method is applied to image segmentation, which is implemented automatically by autonomously clustering the pixels according to their gray values. The optimi...
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ISBN:
(纸本)9780819469502
In this paper, a SGNN (Self-Generating Neural Network)-based method is applied to image segmentation, which is implemented automatically by autonomously clustering the pixels according to their gray values. The optimization of SGNN is studied to further improve the accuracy and robustness, as well as to reduce the computational complexity of the segmentation. The experimental results show that the optimized SGNN gets better segmentation results and outperforms the existing methods for its distinguished advantages of perfect segmentation without any manual intervention, high self-learning capacity, less computational complexity, robustness to noise, etc. What's more, the experimental results suggest that the proposed method can be widely used in segmentation of all typical images, such as IR (Infrared) images, visible images, X-ray images, and MR (Magnetic Resonance) images.
The error sources of airborne laser measurement device which mainly include laser beam misalignment with respect to scanning mirror, clock error, scanner error and scanner torsion are discussed, and their effects to a...
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ISBN:
(纸本)9780819469502
The error sources of airborne laser measurement device which mainly include laser beam misalignment with respect to scanning mirror, clock error, scanner error and scanner torsion are discussed, and their effects to airborne LIDAR (Light Detection and Ranging) position accuracy are analyzed. Specially, laser beam misalignment's influences to LIDAR scanning line distortion and positioning accuracy are analyzed in detail quantitatively and qualitatively for oscillating scanner. The analysis demonstrates that laser beam misalignment influences the scanning line distortion and positioning accuracy more and more with the increasing height and scanning angle and can't be eliminated by common calibration methods but by the calibration method in factory for it is related to other error sources.
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