Visual tracking, a fundamental task in computer vision, has been criticized less well-posed since reliable target information only given at first frame. In this case, most of the existing template-matching-based track...
ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
Visual tracking, a fundamental task in computer vision, has been criticized less well-posed since reliable target information only given at first frame. In this case, most of the existing template-matching-based trackers fail to locate the target when non-rigid deformations or variations occur. To address these issues, we propose a principled way to take advantage of the superpixel labeling and discriminative tracking algorithms. For each frame, a correlation tracker is first adopted to provide the coarse target location. Afterwards, a collaborative segmentation approach is advocated to segment the surrounding region of the target into superpixels. Target appearance and motion trajectory are considered as spatial and temporal constrains and incorporated into superpixel labeling module. The fine-segmentation result, in turn, provides a more accurate target status for template updating. The effectiveness of the proposed algorithm is validated through experimental comparison on widely-used tracking benchmark datasets.
An anti-retransmitted jamming technique is proposed by utilizing phase and frequency-coded waveform techniques. To generate the effective agility waveforms, improved Logistic-Map chaotic sequences generation and optim...
ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
An anti-retransmitted jamming technique is proposed by utilizing phase and frequency-coded waveform techniques. To generate the effective agility waveforms, improved Logistic-Map chaotic sequences generation and optimization algorithm are proposed to obtain sets of orthogonal polyphase codes. The simulated ambiguity function of the agility waveform shows that the agility waveform presents a high resolution in the range domain. The performance of the waveform under different signal-to-interference ratios(SIR) is analyzed. Compared to conventional LFM waveforms, the agility waveform is capable of suppressing the retransmitted jamming effectively, by up to 30dB when the SIR is -5dB.
Automatical inshore ship change detection in optical remote sensing images is meaningful for a wide range of applications, but still a challenging task. In this paper, a visual search inspired model is proposed for in...
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Automatical inshore ship change detection in optical remote sensing images is meaningful for a wide range of applications, but still a challenging task. In this paper, a visual search inspired model is proposed for inshore ship change detection. The proposed model achieves inshore ship change information extraction based on spatial-temporal saliency detection which mimics visual search mechanism. Experimental results performed on a Google Earth optical remote sensing image data set demonstrate the effectiveness of the proposed model in terms of visual and objective evaluations.
Aircraft detection in optical remote sensing image is an important research direction in the field of remote sensing. The existing detection methods are difficult to achieve satisfactory results. Traditional detection...
ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
Aircraft detection in optical remote sensing image is an important research direction in the field of remote sensing. The existing detection methods are difficult to achieve satisfactory results. Traditional detection methods are low robustness, due to manual feature modeling are difficult and subject to background interference; The deep learning target detection method, which improves the detection performance at the cost of complexity improvement, cannot be widely used in space-borne platforms limited resources. In view of the above problems, this paper proposes an aircraft target deep learning detection method of lightweight and multi-scale features. On the basis of the multi-scale target detection framework (SSD), the method firstly uses the dense connection structure and the double convolution channels to form the basic backbone networks with feature reuse and high computational efficiency. To improve the detection performance of the small aircraft target, the basis backbone network connects a residual module and deconvolution to compose the multi-scale feature fusion detection module. Compared with the current classical deep learning object detection methods, the experimental results show that the proposed method has the advantages of maintaining low computational complexity and achieving high detection accuracy.
With the rapid advancement of optical remote sensing (RS) satellites, RS video has replaced RS image as the main way to obtain information in orbit environment. However, the storage and transmission of on-orbit RS vid...
ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
With the rapid advancement of optical remote sensing (RS) satellites, RS video has replaced RS image as the main way to obtain information in orbit environment. However, the storage and transmission of on-orbit RS video faces enormous challenges: the contradiction between limited power, space and bandwidth and massive video data volume is becoming increasingly acute. To solve this problem, this paper proposes an effective implementation of spaceborne real-time RS video compression based on CPU+GPU heterogeneous framework. First, we propose a new rate control method based on HEVC for on-orbit RS video compression, which allocates less bitrate for low complexity code blocks (CBs) and more bitrate for high complexity CBs, which can improve the accuracy of rate control algorithm while ensuring compression quality. Then this paper makes full use of the CPU + GPU heterogeneous framework to speed up the whole compression processing. The experimental results show that the proposed compression framework realizes 200x real-time compression of 1080p spaceborne RS video with a PSNR greater than 38.7 dB.
In the multi-mode SAR imaging processing targeted in this paper, the FFT requirement granularity ranges from 1024 to 32768. Therefore, this paper mainly describes the method of implementing reconfigurable and variable...
ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
In the multi-mode SAR imaging processing targeted in this paper, the FFT requirement granularity ranges from 1024 to 32768. Therefore, this paper mainly describes the method of implementing reconfigurable and variable-level FFT units using radix-2 k , By analyzing and comparing the radix 2 k algorithm, the radix-2 3 is selected as the basis of the single-channel FFT butterfly, and the range of the point representation is extended by the butterfly transformation downward compatible with the radix-2 2 /radix-2. This paper realizes an architecture of the single channel delay feedback variable-point, high precision FFT processor.
With the development of modern technology, embeddedtechnology has continued to develop. In the deep cooperation between embedded and wireless network technologies, the technology of sensor network has been born. The ...
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作者:
Ying XiHaibo LiuYanhua WangYang LiRadar Research Lab
School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China
Scatter center matching is one of the choke points of radar automatic target recognition (RATR) based on Synthetic Aperture Radar (SAR). Accuracy of scattering center extraction is an important factor affecting target...
ISBN:
(数字)9781728129129
ISBN:
(纸本)9781728129136
Scatter center matching is one of the choke points of radar automatic target recognition (RATR) based on Synthetic Aperture Radar (SAR). Accuracy of scattering center extraction is an important factor affecting target recognition performance. This paper proposes a SAR images scattering center estimation method based on atomic norm minimization (ANM) model. This method models the scattering center estimation problem as a two-dimensional line spectrum estimation problem, then the estimation is performed in a continuous domain via ANM. The experimental results indicate the superiorities of the proposed method in terms of accuracy and robustness.
Unmanned aerial vehicles (UAVs) are now widely used in civil applications. Uncontrolled UAVs may cause some harm to the order of flight fields and other places. An adaptive UAV detection algorithm based on maximally s...
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ISBN:
(数字)9781728123455
ISBN:
(纸本)9781728123462
Unmanned aerial vehicles (UAVs) are now widely used in civil applications. Uncontrolled UAVs may cause some harm to the order of flight fields and other places. An adaptive UAV detection algorithm based on maximally stable extremal regions method is proposed for small target detection of UAV in video. By optimizing the MSER algorithm, this UAV detection algorithm can detect video in realtime and has sufficient robustness. At the same time, we combined discriminative scale space tracker algorithm to test the existing video, and got good real-time performance. Considering the practical application scenarios, we use NVIDIA Jetson TX2 to test the algorithm and collate the results. The results show that our method performs well.
Interferometric Synthetic Aperture Radar(InSAR)has been proposed as a technique for the reconstruction of the Digital Elevation Model(DEM),which is widely used in global terrain mapping mission[1].The DEM reconstructi...
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Interferometric Synthetic Aperture Radar(InSAR)has been proposed as a technique for the reconstruction of the Digital Elevation Model(DEM),which is widely used in global terrain mapping mission[1].The DEM reconstruction methods of In SAR technique are usually based on the so-called phase unwrapping(PU)*** highly sloped terrain,the interferometric phase gradients(IPG)of the adjacent pixels are more thanπ.Therefore,the traditional PU methods
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