Object Relocation Visual Tracking Based On Histogram Filter And Siamese Network

Siamese network based trackers formulate the visual tracking mission as an image matching process by regression and classification branches, which simplifies the network structure and improves tracking accuracy. However, there remain many problems as described below. 1) The lightweight neural networks decreases feature representation ability. The tracker is easy to fail under the disturbing distractors (e.g., deformation and similar objects) or large changes in viewing angle. 2) The tracker cannot adapt to variations of the object. 3) The tracker cannot reposition the object that has failed to track. To address these issues, we first propose a novel match filter arbiter based on the Euclidean distance histogram between the centers of multiple candidate objects to automatically determine whether the tracker fails. Secondly, Hopcroft-Karp algorithm is introduced to select the winners from the dynamic template set through the backtracking process, and object relocation is achieved by comparing the Gradient Magnitude Similarity Deviation between the template and the winners. The experiments show that our method obtains better performance on several tracking benchmarks, i.e., OTB100, VOT2018, GOT-10k and LaSOT, compared with state-of-the-art methods.

Q-interface imaging using accumulative attenuation estimation

A high-resolution Q model is beneficial for more accurate attenuation compensation and preferable for gas-related interpretation. Given an accurate velocity model, viscoacoustic/viscoelastic full-waveform inversion ( Q-FWI) could reconstruct a high-resolution Q model, but it requires significant computational cost due to the iterative process of solving viscoacoustic/viscoelastic wave equations. We have proposed an efficient high-resolution Q-interface imaging method through the following steps. First, we estimate the attenuated traveltime via inversion of the dynamic match filter between synthetic acoustic and observed viscoacoustic prestack records. Second, we derive virtual Q reflectivities via piecewise linear regression on the attenuated traveltime estimation. Finally, by convolving a source wavelet on the virtual Q reflectivities, we generate the virtual Q reflection gathers and migrate them through reverse time migration (RTM) to image the Q interfaces. The Q-interface information is essentially derived by comparing the accumulative attenuation effects estimated from near-offset primary reflections arriving at the same receiver successively in time, and the high resolution is assured by the piecewise linear regression based on prior knowledge of the Q-interface number along the depth. The key insight of our method is to use accumulative attenuation effects to derive immediate effects of Q interfaces (virtual Q reflections) in the prestack data domain, which are readily applicable for Q-interface imaging through simple acoustic RTM. Numerical examples demonstrate that our method produces unprecedented high-resolution images of Q interfaces along the vertical direction with satisfying positioning and interpretable polarity.

Seafloor Erosion induced by overbanking flow derived by a 2.5D high resolution sparker seismic dataset, uppermost Kaoping Submarine Canyon, southwestern offshore Taiwan

<p>The Kaoping submarine canyon (KPSC) originates from Kaoping River, southwestern Taiwan that extends about 250 kilometers long from the Kaoping River mouth down to the Manila Trench. It can be divided into three major sections: upper reach (meandering), middle reach (NW-SE trending and V-shaped canyon) and lower reach (meandering). Based on recent a swath bathymetric data in the uppermost KPSC, an obvious seafloor depression can be observed in the eastern bank of the canyon. The eastern bank of the canyon reveals about 30-50 meters in average lower than western bank. The mechanism is blurred. In this study, to investigate fine sedimentary structures in 3D point of view, we used marine sparker seismic method. The seismic source frequency varies from 100 to 1200 Hz which can provide about 0.6 meters vertical resolution (i.e. central frequency 600 Hz and 1,600 m/s Vp). We have collected 75 in-lines across the canyon and 3 cross-lines perpendicular to the in-line. The data went through conventional marine seismic data processing procedures such as bad trace kill, band-pass filter, 2D geometry settings, NMO stacking, swell correction, match filter and predictive deconvolution. The 2D dataset was reformatted by applying 3D geometry settings to create a 3D seismic cube. The result shows that a wide incision channel was first found in the north of Xiaoliuchiu islet. Through depth, this channel becomes two narrower channels divided by a mud diapir. This down cutting can be traced down to transgressive sequence in prior to LGM (Last Glacial Maximum). In addition, a deep-towed sub-bottom profiler shows an obvious down-lapping structures heading off canyon that indicates over banking flow may be a key role to cause this erosional event.</p>

Optimizing Transmit Sequence and Instrumental Variables Receiver for Dual-Function Complexity System

This correspondence deals with the joint cognitive design of transmit coded sequences and instrumental variables (IV) receive filter to enhance the performance of a dual-function radar-communication (DFRC) system in the presence of clutter disturbance. The IV receiver can reject clutter more efficiently than the match filter. The signal-to-clutter-and-noise ratio (SCNR) of the IV filter output is viewed as the performance index of the complexity system. We focus on phase only sequences, sharing both a continuous and a discrete phase code and develop optimization algorithms to achieve reasonable pairs of transmit coded sequences and IV receiver that fine approximate the behavior of the optimum SCNR. All iterations involve the solution of NP-hard quadratic fractional problems. The relaxation plus randomization technique is used to find an approximate solution. The complexity, corresponding to the operation of the proposed algorithms, depends on the number of acceptable iterations along with on and the complexity involved in all iterations. Simulation results are offered to evaluate the performance generated by the proposed scheme.

Automatic detection and extraction algorithm of coronal loops based on match filter and oriented directivity

ABSTRACT In this paper, an efficient algorithm is developed to automatically detect and extract coronal loops. First of all, in the algorithm, three characteristics associated with coronal loops are used to construct a match filter able to enhance the loops. Secondly, the method combining a high-pass filter (unsharp-mask enhancement) with a global threshold is used to further enhance and segment the loops. Thirdly, to extract every individual coronal loop and obtain their parameters (the 2D projected space coordinates and lengths) from the segmented loops, a clustering method of the pixels with approximate local direction and connected domain is further used. Fourthly, to evaluate the performance of the developed algorithm, images observed by the Transition Region and Coronal Explorer (TRACE), the Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO) and the High-Resolution Coronal Imager (Hi-C) are used, and comparison experiments between the existing algorithms and the developed algorithm are performed. Finally, it is found that the developed algorithm is commensurate with the two most promising algorithms, oriented coronal curved loop tracing (OCCULT) and its improved version, OCCULT-2, in performance. Therefore, for scientific applications associated with coronal loops, the developed algorithm will be a powerful tool.

2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar

Long time coherent integration is a vital method for improving the detection ability of global navigation satellite system (GNSS)-based passive radar, because the GNSS signal is not radar-designed and its power level is very low. For aircraft detection, the large range cell migration (RCM) and Doppler frequency migration (DFM) will seriously affect the coherent processing of azimuth signals, and the traditional range match filter will also be mismatched due to the Doppler-intolerant characteristic of GNSS signals. Accordingly, the energy loss of 2-dimensional (2-D) coherent processing is inevitable in traditional methods. In this paper, a novel 2-D coherent integration processing and algorithm for aircraft target detection is proposed. For azimuth processing, a modified Radon Fourier Transform (RFT) with range-walk removal and Doppler rate estimation is performed. In respect to range compression, a modified matched filter with a shifting Doppler is applied. As a result, the signal will be accurately focused in the range-Doppler domain, and a sufficiently high SNR can be obtained for aircraft detection with a moving target detector. Numerical simulations demonstrate that the range-Doppler parameters of an aircraft target can be obtained, and the position and velocity of the aircraft can be estimated accurately by multiple observation geometries due to abundant GNSS resources. The experimental results also illustrate that the blind Doppler sidelobe is suppressed effectively and the proposed algorithm has a good performance even in the presence of Doppler ambiguity.