With the increasing popularity of mobile devices, there are more and more screens with heterogeneous resolutions. In order to solve the mismatching problem of images displaying on different screens, various image reta...
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ISBN:
(纸本)9781479989591
With the increasing popularity of mobile devices, there are more and more screens with heterogeneous resolutions. In order to solve the mismatching problem of images displaying on different screens, various image retargeting techniques have been proposed. However, little effective objective quality assessment metric for image retargeting has been proposed. In this paper, we propose an objective image retargeting quality assessment method based on Hybrid Distortion Pooled Model (HDPM) considering image local similarity, content information loss and image structural distortion. The proposed HDPM method measures the retargeted image's local similarity based on matching the similar block by Scale-Invariant Features Transform (SIFT) features and computing the corresponding blocks' similarity by structural similarity (SSIM). Furthermore, the image content information loss in retargeted image, which is regarded as the SIFT feature loss, is taken into account. Besides, we also consider image's structural distortion in the proposed method, which is based on GLCM (Gray-level co-occurrence matrix). To evaluate the effectiveness of the proposed method, extensive experiments have been conducted, and the results show improved consistency between the proposed HDPM method and the corresponding subjective evaluations.
In the era of cloud computing, there are many correlated images in the cloud, joint compression of these images may provide much higher compression ratio than individual coding. Model-based coding is an appealing appr...
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ISBN:
(纸本)9781479986897
In the era of cloud computing, there are many correlated images in the cloud, joint compression of these images may provide much higher compression ratio than individual coding. Model-based coding is an appealing approach to image coding in the cloud, as it removes knowledge redundancy among images that share the same model. In this paper, we make an attempt to model-based image coding for landmark images, where our model consists of three-dimensional (3-D) point-cloud plus image patches to describe the geometry and surface color of the landmark respectively. The camera parameters of an input image are estimated based on the 3-D point-cloud and the patches in the model, and then prediction image is generated by selecting, warping, and stitching image patches as well as illuminance compensation, the residue between original and prediction images is compressed by P-frame coding in HEVC encoder. We perform experiments on an Internet photo collection to verify the effectiveness of the proposed scheme. Preliminary results display the superior performance of our scheme that achieves as high as 39.9% bits saving compared to HEVC intra on a single image. The proposed scheme indicates a promising approach to image coding in the cloud and is worthy of in-depth investigation.
In recent years, the Total Generalized Variation (TGV) model has received lots of attention in image processing community. Though this model can restore image with natural intensity transitions, its spatial identical ...
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In recent years, the Total Generalized Variation (TGV) model has received lots of attention in image processing community. Though this model can restore image with natural intensity transitions, its spatial identical parameter setting limits its performance. In this paper, we propose a novel Adaptive Weighted Total Generalized Variation model for image restoration. We analyze the TGV model from Bayesian Probability view and derive a novel adaptive parameter calculation scheme for it, exploiting the image's self-similarity. Experiment results on image deblurring and reconstruction show that by adapting the parameters in TGV model to image contents, the proposed model can restore image's edges and details well and achieve significant improvement over state of the art variational based models.
Bundle adjustment with additional parameters is identified as a critical step for precise orthoimage generation and 3D reconstruction of Dunhuang wall paintings. Due to the introduction of self-calibration parameters ...
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The Asia-Pacific(AP)region has experienced faster warming than the global average in recent decades and has experienced more climate extremes,however little is known about the response of vegetation growth to these **...
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The Asia-Pacific(AP)region has experienced faster warming than the global average in recent decades and has experienced more climate extremes,however little is known about the response of vegetation growth to these *** updated Global Inventory Modeling and Mapping Studies third-generation global satellite Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index dataset and gridded reanalysis climate data were used to investigate the spatiotemporal changes in both trends of vegetation dynamic indicators and climatic *** then further analyzed their relations associated with land cover across the AP *** main findings are threefold:(1)at continental scales the AP region overall experienced a gradual and significant increasing trend in vegetation growth during the last three decades,and this NDVI trend corresponded with an insignificant increasing trend in temperature;(2)vegetation growth was negatively and significantly correlated with the Pacific Decadal Oscillation index and the El Niño/Southern Oscillation(ENSO)in AP;and(3)at pixel scales,except for Australia,both vegetation growth and air temperature significantly increased in the majority of study regions and vegetation growth spatially correlated with temperature;In Australia and other water-limited regions vegetation growth positively correlated with precipitation.
The scalable and multiview extensions of the High Efficiency Video Coding share the same high-level syntax coding structure. For the scalable extension, the motion field of the inter-layer reference picture is modifie...
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ISBN:
(纸本)9781479983926
The scalable and multiview extensions of the High Efficiency Video Coding share the same high-level syntax coding structure. For the scalable extension, the motion field of the inter-layer reference picture is modified through Motion Field Mapping before used for motion vector prediction. However, the motion field of the inter-layer reference picture is used without modification in the multiview extension. In this paper, a disparity-compensated inter-layer motion prediction is proposed for multiview video coding to achieve disparity compensation in inter-layer motion prediction using the scaled reference layer offset. The experimental results show that comparing with the multiview extension anchor, the proposed method achieves an average of 1.1% bitrate reduction.
Network predictive control is effectively in dealing with time-delay, data dropouts, packets disorders of Network Control system. This paper studies the stochastic stability of a affine nonlinear system within random ...
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ISBN:
(纸本)9781467374439
Network predictive control is effectively in dealing with time-delay, data dropouts, packets disorders of Network Control system. This paper studies the stochastic stability of a affine nonlinear system within random time delay. The system controller is consist of a control prediction generator(CPG) at the controller side and a network delay compensator(NDC) at the plant side. Different from the previous literatures that model the random delay of the feedback channel and the forward channel as Markov chain respectively, the model in this paper is based on the round-trip delay, which making the predictive control process more concise but without losing generality. Then, this paper gives the necessary and sufficient conditions for stochastic stability of the closed-loop system. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.
Block-wise compressed image often suffers from the blocking artifacts. In this paper, we propose a novel deblocking scheme for compressed image, by combining image's sparse property and its self-similarity togethe...
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ISBN:
(纸本)9781479983926
Block-wise compressed image often suffers from the blocking artifacts. In this paper, we propose a novel deblocking scheme for compressed image, by combining image's sparse property and its self-similarity together, called group sparsity optimization. Instead of processing each image patch individually, in the proposed scheme, similar patches in one group are required to be well-represented on learned dictionary collaboratively, using group sparsity regularization. The group sparsity not only imposes every patch's representation to be sparse, bus also requires patches' coefficients in the group share the similar pattern. The experiment results on standard test images demonstrate that our scheme can improve the PSNR of the compressed images by an average of 1.25 dB, and outperform state of the art deblocking approaches.
This paper introduces a novel global patch matching method that focuses on how to remove fronto-parallel bias and obtain continuous smooth surfaces with assuming that the scenes covered by stereos are piecewise contin...
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Network predictive control is effectively in dealing with time-delay, data dropouts, packets disorders of Network Control system. This paper studies the stochastic stability of a affine nonlinear system within random ...
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