The continuous network design problem refers to optimizing the performance of the whole system by increasing the capacity of existing links. In this study, a continuous road network planning model is established consi...
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Content Based image Retrieval is very hottest research area in computer vision and imageprocessing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing...
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ISBN:
(纸本)9781479972081
Content Based image Retrieval is very hottest research area in computer vision and imageprocessing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing research area. Neural Network is a grid of " neuron like" nodes, in this paper we follow towards Neural Network (NN), is committed to contributing a new technical concept for the scene understanding and recognition by consolidating new intellectual visual features into the scene expression, which can be very crucial and provide cognitive intelligence to cloud robot. Inspired by Artificial Neural Network intelligence due to its dynamic nature, we make use of the attributes of the Gabor filter and Laplacian of Gaussian filter which is to be akin to robot visual perception, and apply the wavelet transform to inspect a new approach in complex environment natural scene perception and understanding for virtual phenomena. Through the study of Neural Network, the perception ability of the natural scene image from complex environment for cloud robot is enhanced with the integration of cognitive visual features and the scene expression.
In this work, a closed form solution in the M step of the Expectation Maximization (EM) algorithm is investigaed for learning of unknown image and blur parameters. Cholesky factorization is used to find autoregressive...
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Matching pursuits is an overcomplete expansion technique which has been successfully applied to the problem of coding motion residual images in a hybrid video coder. In this paper, the coding efficiency and decoder co...
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ISBN:
(纸本)0818688211
Matching pursuits is an overcomplete expansion technique which has been successfully applied to the problem of coding motion residual images in a hybrid video coder. In this paper, the coding efficiency and decoder complexity of the method are compared to that of the DCT-based MPEG-4 standard with and without post-processing. Without postprocessing, matching pursuits is shown to have significantly better PSNR and visual quality and similar decoding complexity compared to the MPEG-4 DCT decoder. To achieve reasonable quality at low bit rates, the DCT-based scheme requires post-processing, while the patching pursuit scheme does not. We show that the MPEG-4 post-processing filters have a prohibitive cost, increasing decoder complexity by a factor of 3 to 8. Finally, we introduce an all-integer matching pursuit implementation. Performance is shown to be within 0.05 dB of the original floating point algorithm.
In this paper we present our work in the field of accessibility to visual information in digital documents for the blind people. Our method consists in detecting the significant visual information in a picture/documen...
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ISBN:
(纸本)9781424438334
In this paper we present our work in the field of accessibility to visual information in digital documents for the blind people. Our method consists in detecting the significant visual information in a picture/document, extracting their properties and rearrange them for the specified accessible output. Our approach relies on the efforts made in the field of digital documents accessibility along with imageprocessing and content-based image retrieval. Our system provides then two possibilities of outputs: tactile/oral or a combination of the two.
Mutual Information (MI) is one of the main methods for efficient registration of multiband images in the literature. Since images on different bands are often expressed in different numbers of bits, contrast enhanceme...
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ISBN:
(纸本)9781509064946
Mutual Information (MI) is one of the main methods for efficient registration of multiband images in the literature. Since images on different bands are often expressed in different numbers of bits, contrast enhancement is inevitable before MI-based image registration. Although the contrast enhancement method used has a significant effect on the registration performance due to MI metric, this problem is not sufficiently addressed in the literature. In this paper, the effect of the outstanding contrast enhancement methods is examined on image registration performance. For this purpose, 16-bit thermal and 8-bit visible band satellite images were used and Monte Carlo tests were performed. First, random rotation and translation is applied to the image which is converted from 16-bit to 8-bit by contrast enhancement methods, then the transformation is tried to be estimated with MI and Multi-Level Single-Linkage (MLSL) optimization algorithm. Consequently, it is found that contrast enhancement methods have an effect on MI based image registration. Contrast limited adaptive histogram equalization (CLARE) and AHE methods have the highest registration performance according to the tests performed.
This paper commits to remove the stripe noise to enhance the visual quality of remote sensing images, in the meanwhile preserves image details of stripe-free regions. Instead of solving the underlying image as most of...
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ISBN:
(纸本)9781509021758
This paper commits to remove the stripe noise to enhance the visual quality of remote sensing images, in the meanwhile preserves image details of stripe-free regions. Instead of solving the underlying image as most of researches, we propose a non-convex l(0) model for remote sensing image destriping by taking full consideration of the intrinsically directional and structural priors of stripe noise. Moreover, the proposed non convex model can be solved by the proximal alternating direction method of multipliers (PADMM) method which theoretically guarantees converging to a KKT point. Extensively experimental results on simulated and real data demonstrate that the proposed method outperforms recent state-of-the-art destriping methods, both visually and quantitatively.
Fisher vector coding methods have been demonstrated to be effective for image classification. With the help of convolutional neural networks (CNN), several Fisher vector coding methods have shown state-of-the-art perf...
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ISBN:
(纸本)9781509053162
Fisher vector coding methods have been demonstrated to be effective for image classification. With the help of convolutional neural networks (CNN), several Fisher vector coding methods have shown state-of-the-art performance by adopting the activations of a single fully-connected layer as region features. These methods generally exploit a diagonal Gaussian mixture model (GMM) to describe the generative process of region features. However, it is difficult to model the complex distribution of high-dimensional feature space with a limited number of Gaussians obtained by unsupervised learning. Simply increasing the number of Gaussians turns out to be inefficient and computationally impractical. To address this issue, we re-interpret a pre-trained CNN as the probabilistic discriminative model, and present a CNN based Fisher vector coding method, termed CNN-FVC. Specifically, activations of the intermediate fully-connected and output soft-max layers are exploited to derive the posteriors, mean and covariance parameters for Fisher vector coding implicitly. To further improve the efficiency, we convert the pre-trained CNN to a fully convolutional one to extract the region features. Extensive experiments have been conducted on two standard scene benchmarks (i.e. SUN397 and MIT67) to evaluate the effectiveness of the proposed method. Classification accuracies of 60.7% and 82.1% are achieved on the SUN397 and MIT67 benchmarks respectively, outperforming previous state-of-the-art approaches. Furthermore, the method is complementary to GMM-FVC methods, allowing a simple fusion scheme to further improve performance to 61.1% and 83.1% respectively.
As part of a program of work to explore video compression, the author has studied various aspects of human visual perception and modelling. Tests have been devised to evaluate visual acuity to dynamic effects on both ...
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ISBN:
(纸本)0780332598
As part of a program of work to explore video compression, the author has studied various aspects of human visual perception and modelling. Tests have been devised to evaluate visual acuity to dynamic effects on both interlaced and progressively scanned video. The results of these tests indicate that the visual sensitivity to dynamic errors is substantially different to static. A further test was devised to explore the aspect of error masking in visual perception. Such masking is widely known in audio coding and also apparent in the Human visual System (HVS). The paper will also describe an error weighting mechanism. based on measurements of the reconstruction error in a compression codec. The effect is most noticeable in systems using high compression ratios. A compensation technique is applied to take advantage of the error weighting with the result of improved picture coding quality. The final part of the paper will describe new work which attempts to measure the HVS characteristic in conjunction with the entropy coding efficiency. The tests reported here attempt to find the optimum quantiser profile from the matching of entropy coding efficiency against HVS response.
In this paper, it is presented the implementation of a fast and versatile system with software defined radio, that contains data processing and radio communication algorithms, using the processing power of the integra...
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ISBN:
(纸本)9781728156118
In this paper, it is presented the implementation of a fast and versatile system with software defined radio, that contains data processing and radio communication algorithms, using the processing power of the integrated system on chip and the flexibility introduced by the programmable logic. The demonstrator system transmits and receives data - image captures of cars - using the local area wireless 802.11a protocol. The license plates of the cars are extracted and recognized, as part of an identification process that validates our solution.
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