In all of the existing block-based image and video coding standards, blocks are processed in the fixed scan order. Then in HEVC intra coding, intra prediction is always based on the top and/or left neighboring reconst...
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ISBN:
(纸本)9781509053179
In all of the existing block-based image and video coding standards, blocks are processed in the fixed scan order. Then in HEVC intra coding, intra prediction is always based on the top and/or left neighboring reconstructed pixels, which incurs less accurate prediction for blocks where the spatial correlation is not along the topleft-to-bottomright direction. To obtain better intra prediction, we propose to flexibly determine the coding order of blocks in HEVC intra coding. Complying with the hierarchical quadtree structure in HEVC, our flexible block ordering (FBO) technique recursively decides the coding order of four sub-blocks when splitting one block. Moreover, we propose new methods to perform inter/extrapolation for intra prediction so as to fully utilize neighboring reconstructed pixels, not always being top/left. Experimental results show that our proposed FBO technique achieves on average 2.9% BD-rate reduction compared to HEVC baseline.
Discrete Cosine Transform (DCT) has been the commonly used transform for a few decades in image/video coding. However, DCT does not work well on the blocks having anisotropic correlations. In this paper, based on the ...
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ISBN:
(纸本)9781479953424
Discrete Cosine Transform (DCT) has been the commonly used transform for a few decades in image/video coding. However, DCT does not work well on the blocks having anisotropic correlations. In this paper, based on the adaptive dictionary, we propose a new online transform scheme using Orthogonal Matching Pursuit (OMP) for High Efficiency Video Coding (HEVC). For a coding block, we construct its dictionary by exploiting non-local correlations from the reconstructed regions. The OMP algorithm is implemented to obtain the sparse transform coefficients. Experimental results show that the BD-rate savings of the proposed scheme for the sequences with strong edges can be up to 19.9%.
We propose a novel superpixel algorithm based on Minimum Spanning Tree (MST), to generate superpixels efficiently while strictly adhere to object boundaries. The MST, which built by gradually removing strong edges of ...
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ISBN:
(纸本)9781467372596
We propose a novel superpixel algorithm based on Minimum Spanning Tree (MST), to generate superpixels efficiently while strictly adhere to object boundaries. The MST, which built by gradually removing strong edges of the image graph extracted from the image, is more sensitive to image local structures. Therefore, an efficient hierarchical clustering strategy is basically employed in our algorithm to segment the input image into superpixels based on the tree distance. To gradually merge the image pixels and remove texture noises, a multi-layer scheme with different resolutions of superpixels is proposed. In each layer, the graph is constructed from the lower layer and segmented into superpixels in a linear complexity with the node number in the graph. Because the node number in each layer is exponentially reduced, the computational time of our method mainly concentrates on the first few layers, which is linear with the number of image pixels. The experimental results conducted on the Berkeley Segmentation Dataset demonstrate that our method outperforms state-of-the-art methods both in terms of structure preservation and computational efficiency.
InSAR interferogram quality assessment is a key step for the using of interferogram map. Traditionally, the interferogram is qualitatively assessed visually and quantitatively assessed by the number of residues. Howev...
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InSAR interferogram quality assessment is a key step for the using of interferogram map. Traditionally, the interferogram is qualitatively assessed visually and quantitatively assessed by the number of residues. However, the important structure information is hardly quantifiable. This paper presents a novel index to evaluate the quality of InSAR interferogram based on connected area. After discomposing the fringes into independent connected areas, we analyze the statistical ratio of an area to its margin. Then we use the ratio as an index to quantitatively evaluate the interferogram. In the end, the presented index is used for the filtered interferogram of popular filters, and the results fit the visual judging.
Ionosphere is an important factor in highresolution spaceborne synthetic aperture radar（SAR） and geosynchronous（geo） SAR. An approach based on point target deviation between range sub-images is proposed in this pa...
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Ionosphere is an important factor in highresolution spaceborne synthetic aperture radar（SAR） and geosynchronous（geo） SAR. An approach based on point target deviation between range sub-images is proposed in this paper to estimate and correct the ionosphere. Due to the dispersion effect, the ionosphere causes propagation delay deviation in range subimages with different carrier frequency. This deviation can be used to estimate the total electron content（TEC） along the propagation path, and then the ionospheric effects can be corrected according to the signal model deduced out in this paper. The simulation results show that our approach is valid and robust.
The edges of the shadow region are blurred in the SAR image due to the moving of the radar during data collection. This phenomenon becomes obvious in the High Resolution SAR images. Shadow enhancement is of great valu...
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The edges of the shadow region are blurred in the SAR image due to the moving of the radar during data collection. This phenomenon becomes obvious in the High Resolution SAR images. Shadow enhancement is of great value for ATR especially when the scattering centers of the target itself are not clear. In this paper, an approach for shadow enhancement in the SAR images for targets with plat structures is presented. And experiments on the Mini-SAR data test the validity of the approach.
The massive or large scaled multiple input multiple output(MIMO) systems have gained huge consideration due to high achievable data rates, reliable system performance and advantaged energy efficiency for future wirele...
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ISBN:
(纸本)9781467374439
The massive or large scaled multiple input multiple output(MIMO) systems have gained huge consideration due to high achievable data rates, reliable system performance and advantaged energy efficiency for future wireless networks. For such systems, we should have a keen knowledge of the channel model, the ways of configuration, spectral efficiency and so on. The obtaining of the far-field pattern in the massive MIMO system from measurements made in the near-field has attracted widespread attention recently. In this article, two basic techniques for accomplishing this have been proposed. In the first technique, the NTFF(near-field to far-field) transformation is based on the equivalence principle. While in the second technique, it is based on the plane wave spectrum(PWS) expansion. Both of the methods have their own advantages for the massive MIMO systems. One can drastically reduce the computation time and the other can make enormous reduction in the storage consumption. Experimental results show that the two transformation techniques are proved to be feasible and they are consistent with each other.
Scattering structure features of targets is of great importance for Synthetic Aperture Radar (SAR) image analysis. In this paper, a novel algorithm for aircraft recognition in high resolution apron area of SAR images ...
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ISBN:
(纸本)9781509033331
Scattering structure features of targets is of great importance for Synthetic Aperture Radar (SAR) image analysis. In this paper, a novel algorithm for aircraft recognition in high resolution apron area of SAR images is proposed. The algorithm combines the strength of gradient saliency map and scattering structure features to improve accuracy and efficiency. Specially, Constant False-Alarm Rate (CFAR) algorithm is carried out to segment images. Then, a new efficient object locating method based on directional local gradient map is proposed to detect aircraft targets. Then, the candidate slices as well as template slices are modeled using Gaussian Mixture Model (GMM), which will be treated as structure features. In the recognition stage, a novel similarity measurement algorithm based on Kullback-Leibler Divergence for GMM models is proposed for classification. We conduct experiments on the dataset with 3.0m resolution and the recognition results demonstrate the accuracy of our proposed method.
The intrinsic factors that drive human mobility have remained unclear for decades. Our observations from both intra-urban and inter-urban trips demonstrate a general law of human mobility. Specifically, the probabilit...
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The intrinsic factors that drive human mobility have remained unclear for decades. Our observations from both intra-urban and inter-urban trips demonstrate a general law of human mobility. Specifically, the probability that a trip will occur is inversely proportional to the size of population located inside a circle with radius equal to the travel distance centered at the trip origin. A simple parameterless rank-based model is presented; this model can predict human flows with a convincing fidelity. Moreover, existing models can be implemented as special cases of our model, suggesting that our model is stable at more spatial scales. Our model also creates a fundamental bridge between individual mobility and social relationships.
To avoid distortion, the quantization is not implemented on residues for lossless mode in HEVC. As a result, the conventional lambda model in Rate-Distortion Optimization (RDO), where lambda is related to the quantiza...
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