In this paper we propose PHOTO (pyramid histogram of topics), a new representation for image classification. We partition the image into hierarchical cells and learn the topic histogram using pLSA over each cell with ...
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In this paper we propose PHOTO (pyramid histogram of topics), a new representation for image classification. We partition the image into hierarchical cells and learn the topic histogram using pLSA over each cell with EM algorithm. Then we concatenate the topic histograms over the cells at all levels to form a ldquolongrdquo vector, i.e. pyramid histogram of topics. Finally AdaBoost classifiers are used to select the topics most discriminative for class recognition. Experimental results on two diverse databases show that our method performs significantly better than general topic representation.
An efficient fast inter mode decision algorithm for the baseline H.264/AVC video coding is proposed in this paper. The main idea of the algorithm is to reduce the number of candidate modes for rate distortion optimiza...
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An efficient fast inter mode decision algorithm for the baseline H.264/AVC video coding is proposed in this paper. The main idea of the algorithm is to reduce the number of candidate modes for rate distortion optimization (RDO) by using early mode detection in four different levels, viz. SKIP mode detection, type detection at macroblock-level, type detection at submacroblock-level and intra modes detection. In addition, the correlation of cost of current MB and the one of previous frame, as well as the cost's monotonous property are both used to help the mode decision. Compared to JM8.6 reference software, our algorithm can save encoding time 71.743% on average with negligible PSNR loss, which is very helpful for H.264/AVC inter frame. encoding.
This paper proposes a new image denoising method based on the NonsubSampled Contourlet Transform (NSCT) and the bivariate model under the framework of Bayesian MAP estimation theory. The proposed algorithm uses the NS...
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This paper proposes a new image denoising method based on the NonsubSampled Contourlet Transform (NSCT) and the bivariate model under the framework of Bayesian MAP estimation theory. The proposed algorithm uses the NSCT's advantages of translation-invariant and multidirection-selectivity, exploits the intra-scale and inter-scale correlations of NSCT coefficients, and elaborates the method of noise estimation. Compared with some current outstanding denoising methods, the simulation results and analysis show that the proposed algorithm obviously outperforms in both Peak Signal-to-Noise Ratio (PSNR) and visual quality, and effectively preserves detail and texture information of original images.
Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT)...
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Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT) is proposed, which provides better directionality and approximate shift invariance. By space mapping for the texture image, then complex Directionlet transform is applied to the mapped image, and the multiscale subband coefficient energy feature is used for texture classification. The experiments using texture images from Brodatz and real SAR images indicate the proposed method outperforms wavelets and Multiscale Geometric Analysis (MGA) approaches, the potential application to image analysis by Directionlet is thus proved.
Bandelet transform is an efficient image sparse representation approach which can adaptively approximate the geometrical regularity of image structures. In this paper, a multi-bandelets based method for SAR image comp...
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Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature (BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray ...
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Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature (BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray code of bit-planes is used to avoid the effect of changes in the intensity values on bit-planes. Then, according to the distribution of each bit-plane, a feature vector is constructed by the first four significant planes which contain most of the structural information of the image. Finally, the Mahalanobis distance is adopted to measure the similarity because of the correlation between the concerned vectors after designing a correlation-weighted matrix. Comparisons are conducted between BPDF and other descriptors. Experimental results show that the proposed method provides more significantly retrieval results than the traditional ones.
In this paper, we propose a method based on both 3D-SPECK (3D Set Partitioning Embedded Block) and the theory of DSC (Distributed Source Coding) to realize the compression of hyperspectral images. Some experiments hav...
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This paper proposes a novel model, the mission oriented model, for the problem of land-based satellite tracking telemetry and command (TT&C) resources scheduling. Compared to other models, the mission oriented mod...
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This paper proposes a novel model, the mission oriented model, for the problem of land-based satellite tracking telemetry and command (TT&C) resources scheduling. Compared to other models, the mission oriented model constrains a satellite to be tracked and commanded by only a ground station which can observe the satellite. Therefore, the proposed model makes it possible that scheduling algorithms schedule TT&C resources to complete more missions. Then it proposes the clonal selection land-based satellite TT&C resources scheduling algorithm (CS_STT&CRSA) based on the mission oriented model and proves its global convergence in theory. The algorithm adopts a matrix coding scheme, which depends on the start times of tracked and commanded orbits and the relationships between satellites and ground stations. The severe-constraint satisfaction operator which guarantees the individual satisfies severe constraints is proposed. When there are 5 geostationary satellites and 30, 40 or 50 low earth orbit and medium earth orbit (LEO&MEO) satellites, 10 different groups of tasks are generated respectively. Experimental results illustrate that the mission oriented model enables scheduling algorithms to make better use of TT&C resources and complete more missions and CS_TT&CRSA has more powerful ability of searching and solving constraints and is more stable.
Because of noise and clutter, the infrared target detection even becomes more difficult. In this paper, we present an automatic seed selection method based on an improved mountain cluster algorithm to be employed in i...
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A novel analytic approach is presented to study the population of excitatory and inhibitory spiking neurons in this paper. The evolution in time of the population dynamic equation is determined by a partial differenti...
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A novel analytic approach is presented to study the population of excitatory and inhibitory spiking neurons in this paper. The evolution in time of the population dynamic equation is determined by a partial differential equation. A new function is proposed to characterize the population of excitatory and inhibitory spiking neurons, which is different from the population density function discussed by most researchers. And a novel evolution equation, which is a nonhomogeneous parabolic type equation, is derived. From this, the stationary solution and the firing rate of the stationary states are given. Last, by the Fourier transform, the time dependent solution is also obtained. This method can be used to analyze the various dynamic behaviors of neuronal populations.
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