The real-time mapping of street atmospheric pollution concentration does play an important role because its knowledge is crucial for strategy-makers to make more effective control strategies to decrease urban atmosphe...
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ISBN:
(纸本)9781509017300
The real-time mapping of street atmospheric pollution concentration does play an important role because its knowledge is crucial for strategy-makers to make more effective control strategies to decrease urban atmospheric pollution and improving urban atmospheric environment. Combining the conventional methods (e.g. the dispersion model prediction and neural network prediction) and mobile measurement technology (e.g. the GMAP vehicle) which their characteristics are complementary, a linear model is proposed and then a fusion approach called weighting filter derived from the concept of Kalman filter. Moreover, a self-tuning regulator is introduced to adjust the parameters of filter for the changing noise statistical characteristics over time which mainly caused by season switch. The performances of asymptotic stability and asymptotic optimality are both mathematically proven. Finally a simulation test is conducted to verify this approach.
A cepstrum moving target detection （CEPMTD） algorithm based on cepstrum techniques is proposed for passive coherent location （PCL） radar systems. The primary cepstrum techniques are of great success in recognizing...
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A cepstrum moving target detection （CEPMTD） algorithm based on cepstrum techniques is proposed for passive coherent location （PCL） radar systems. The primary cepstrum techniques are of great success in recognizing the arrival times of static target echoes. To estimate the Doppler frequencies of moving targets, we divide the radar data into a large number of seg- ments, and reformat these segments into a detection matrix. Applying the cepstrum and the Fourier transform to the fast and slow time dimensions respectively, we can obtain the range information and Doppler information of the moving targets. Based on the CEPMTD outlined above, an improved CEPMTD algorithm is proposed to improve the detection performance. Theoretical analyses show that only the target＇s peak can be coherently added. The performance of the improved CEPMTD is initially vali- dated by simulations, and then by experiments. The simulation results show that the detection performance of the improved CEPMTD algorithm is 13.3 dB better than that of the CEPMTD algorithm and 6.4 dB better than that of the classical detection algorithm based on the radar cross ambiguity function （CAF）. The experiment results show that the detection performance of the improved CEPMTD algorithm is 1.63 dB better than that of the radar CAF.
This paper presents a new Synthetic Aperture Radar（SAR） Automatic Target Recognition（ATR） method based on slow feature analysis. Slow feature analysis（SFA） is a method for learning invariant or slowly varying fe...
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This paper presents a new Synthetic Aperture Radar（SAR） Automatic Target Recognition（ATR） method based on slow feature analysis. Slow feature analysis（SFA） is a method for learning invariant or slowly varying features from multi-dimensional input signal. The SFA-based SAR ATR system does not require any pre-processing, such as filtering or pose estimation of the image. The performance of the method is evaluated via three classification experiments on Moving and Stationary Target Acquisition and Recognition（MSTAR） database. The experiment results show the effectiveness of the proposed method on SAR ATR problem.
The Dynamic Adaptive Streaming over HTTP (DASH) enables bitrate adaptation through different representations of the same content. It is common to encode random access point (RAP) pictures at segment boundaries to supp...
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ISBN:
(纸本)9781479983407
The Dynamic Adaptive Streaming over HTTP (DASH) enables bitrate adaptation through different representations of the same content. It is common to encode random access point (RAP) pictures at segment boundaries to support representation switching. As an open group of pictures (GOP) results into a temporary discontinuity of the video playback due to the inability to decode some pictures when switching representations, closed GOP prediction structures are normally used in DASH. This paper proposes two similar methods for using the open GOP prediction structure in DASH representations while a full picture rate is maintained also during representation switching. The first method is enabled with straightforward changes in the decoding of the High Efficiency Video Coding (H.265/HEVC) standard, whereas the second method utilizes the adaptive resolution change feature of the scalable (SHVC) extension of H.265/HEVC. Experiments show that the proposed methods outperform the use of closed GOPs by 5.6% on average in terms of Bjontegaard delta bitrate (BD-rate).
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.
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