In this paper a dim point target detection algorithm based on Markov Random Field (MRF) is proposed. Firstly, the Min-Difference Filter (MDF) is applied to suppress the background in each single frame. Then an adaptiv...
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ISBN:
(纸本)9781467359177
In this paper a dim point target detection algorithm based on Markov Random Field (MRF) is proposed. Firstly, the Min-Difference Filter (MDF) is applied to suppress the background in each single frame. Then an adaptive segmentation process based on 3D MRF is used to detect targets in image sequence. Unlike the traditional 3D MRF, the spatial MRF is modified and a Point-to-Region mapping according to the specific situation is proposed. Experiment results show that the proposed algorithm allows to detect IR point targets in complex backgrounds.
In this paper, we introduce a radon wigner ville based image dissimilarity measure. The proposed image distortion measure aims to combine the useful properties of the wigner ville and the directionality of the finite ...
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We propose a novel and efficient SAR image despeckling via bivariate shrinkage based on contourlet transform, which has been recently introduced. Contourlet transform is a flexible multi-scale, multi-direction and mul...
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ISBN:
(纸本)9780769533117
We propose a novel and efficient SAR image despeckling via bivariate shrinkage based on contourlet transform, which has been recently introduced. Contourlet transform is a flexible multi-scale, multi-direction and multi-resolution image decomposition that can be efficiently implemented via transform. A bivariate shrinkage with local variance estimation is applied to the decomposed contourlet coefficients of the logarithmically transformed image to estimate the best value for the noise-free signal. Experimental results show that compared with conventional wavelet despeckling algorithm, the proposed algorithm can achieve an excellent balance between suppresses speckle effectively and preserves image details, and the significant information of original image like textures and contour details is well maintained.
In this paper an algorithm to cluster face images found in video sequences is proposed. A novel method for creating a dissimilarity matrix using SIFT image features is introduced. This dissimilarity matrix is used as ...
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ISBN:
(纸本)9781424407071
In this paper an algorithm to cluster face images found in video sequences is proposed. A novel method for creating a dissimilarity matrix using SIFT image features is introduced. This dissimilarity matrix is used as an input in a hierarchical average linkage clustering algorithm, which yields the clustering result. Three well known clustering validity measures are provided to asses the quality of the resulting clustering, namely the F measure, the overall entropy (OE) and the Gamma statistic. The final result is found to be quite robust to significant scale, pose and illumination variations, encountered in facial images.
Discrete signalprocessing using fuzzy fractal dimension and grade of fractality is proposed based on the novel concept of merging fuzzy theory and fractal theory. The fuzzy concept of fractality, or self-similarity, ...
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ISBN:
(纸本)9781424407071
Discrete signalprocessing using fuzzy fractal dimension and grade of fractality is proposed based on the novel concept of merging fuzzy theory and fractal theory. The fuzzy concept of fractality, or self-similarity, in discrete time series can be reconstructed as a fuzzy-attribution, i.e., a kind of fuzzy set. The objective short time series can be interpreted as an objective vector, which can be used by a newly proposed membership function. Sliding measurement using the local fuzzy fractal dimension (LFFD) and the local grade of fractality (LGF) is proposed and applied to fluctuations in seawater temperature around the Izu peninsula of Japan. Several remarkable characteristics are revealed through "fuzzy signalprocessing" using LFFD and LGF.
representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene,...
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In this paper, a novel color image quantization algorithm is presented. This new algorithm addresses the question of how to incorporate the principle of human visual perception to color variation sensitivity into colo...
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ISBN:
(纸本)9781424407071
In this paper, a novel color image quantization algorithm is presented. This new algorithm addresses the question of how to incorporate the principle of human visual perception to color variation sensitivity into color image quantization process. Color variation measure (CVM) is calculated first in CIE Lab color space. CVM is used to evaluate color variation and to coarsely segment the image. Considering both color variation and homogeneity of the image, the number of colors that should be used for each segmented region can be determined. Finally, CF-tree algorithm is applied to classify pixels into their corresponding palette colors. The quantized error of our proposed algorithm is small due to the combination of human visual perception and color variation. Experimental results reveal the superiority of the proposed approach in solving the color image quantization problem.
In the area of content based image retrieval, people always use the image similarity based on the concrete image parameters like color to rank the images. However the ranking criteria based on image similarity directl...
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In the automotive sector a huge amount of measurement data is recorded for validation and safeguarding of vehicle components. These data has to be automatically evaluated for an effective data analysis. Therefore, we ...
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ISBN:
(纸本)9781424407071
In the automotive sector a huge amount of measurement data is recorded for validation and safeguarding of vehicle components. These data has to be automatically evaluated for an effective data analysis. Therefore, we need a sophisticated approach, which offers a flexible and powerful parametrisation and different signalprocessing algorithms for multiple applications. In this paper software and signal evaluation modules for an automated analysis of vehicle measurement data are presented. The data can be evaluated signal or message based with a parametrisation with reusable XML templates. Exemplary, we describe three evaluation modules integrating different signalprocessing approaches: signal analysis using an analytical signal description in combination with fuzzy logic, an efficient sliding frequency detection and the detection of predefined patterns using a modified dynamic time warping algorithm. Furthermore, an approach for a connected evaluation in consideration of time correlation is presented. Concluding, we discuss a practical application.
In this paper a method for image segmentation using an opposition-based reinforcement learning scheme is introduced. We use this agent-based approach to optimally find the appropriate local values and segment the obje...
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ISBN:
(纸本)9781424407071
In this paper a method for image segmentation using an opposition-based reinforcement learning scheme is introduced. We use this agent-based approach to optimally find the appropriate local values and segment the object. The agent uses an image and its manually segmented version and takes some actions to change the environment (the quality of segmented image). The agent is provided with a scalar reinforcement signal as reward/punishment. The agent uses this information to explore/exploit the solution space. The values obtained can be used as valuable knowledge to fill the Q-matrix. The results demonstrate potential for applying this new method in the field of medical image segmentation.
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