-
Record 157 of
Title:The digital simulation of end-To-end imaging chain in optical remote sensing system based on MTF models
Author(s):Bu, Fan(1); Yao, Dalei(1); Qiu, Yuehong(1); Jiang, Baotan(1)
Source: Proceedings of 2015 4th International Conference on Computer Science and Network Technology, ICCSNT 2015 Volume: Issue: DOI: 10.1109/ICCSNT.2015.7490762 Published: June 13, 2016
Abstract:The conflicts between the miniaturization of optical remote sensor and the high resolution force us to build an end-To-end simulation system, and optimize the process of the image acquisition and processing. In this paper, based on the analysis of MTF models of each link in imaging chain, a scientific visualization method of end-To-end optical remote sensing process using MTF models is presented. And, imaging simulation software is programmed with Matlab to implement the process. Using this program, the final simulated image can be generated from the original through the whole remote sensing image course according to the input parameters of each link in image chain. Through research on simulated images, we can analyze effectively the effects of each link on the quality of images, and carry out the optimization of optical remote sensor. ? 2015 IEEE.
Accession Number: 20163002647845
-
Record 158 of
Title:Real-fringe DASH interferometer for upper atmospheric wind and temperature observation: Concept and simulation
Author(s):Fei, Xiaoyun(1,2); Feng, Yutao(1); Bai, Qinglan(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 9449 Issue: DOI: 10.1117/12.2075814 Published: 2015
Abstract:Doppler asymmetric spatial heterodyne spectroscopy (DASH) is a new technology for measuring upper atmospheric winds by observing the Doppler shift of atmospheric emission lines from a satellite using a limb viewing geometry. The real-fringe DASH interferometer is a modification of conventional DASH interferometer; it keeps the advantages of the conventional one. Moreover, this interferometer will not need exit optics to image the superposed fringes onto the detector; it will be more compact and lightweight, making it suitable for space-based platforms. We describe the concept of the new interferometer and present the exact expression of spatial frequency and phase of the interferogram. We also describe design and simulation of a real-fringe DASH interferometer for observation of the O [1D] 630nm emission. The simulation results agree with the theory. ? 2015 SPIE.
Accession Number: 20151100635593
-
Record 159 of
Title:Research on the calibration and data retrieval of the wind field measurement Fabry-Perot interferometer
Author(s):Shi, Da-Lian(1,2); Feng, Yu-Tao(1); Zhang, Geng(1); Li, Yong(1); Bai, Qing-Lan(1); Wen, De-Sheng(1)
Source: Guangzi Xuebao/Acta Photonica Sinica Volume: 44 Issue: 8 DOI: 10.3788/gzxb20154408.0812001 Published: August 1, 2015
Abstract:For the work of calibration and data retrieval of the wind field measuring Fabry-Perot interferometer, a method of nonlinear regression fitting combined with transfer function model was researched. First of all, the instrument transfer function and air-glow response model were established with a modified Airy function. Secondly, ground calibration was done to the Fabry-Perot interferometer system with a frequency-stabilized laser and the calibration data was collected. Nonlinear regression fitting step by step was applied to the processing of the calibration data to get parameters of the instrument transfer function. Finally, the wind and temperature of the simulated air-glow fringe, with different signal noise ratio, wind and temperature input, were estimated with the calibrated instrument transfer function model. The results show that the wind and temperature retrieval accuracy can excel 5 m/s and 10 K respectively for data with signal noise ratio better than 40. ?, 2015, Chinese Optical Society. All right reserved.
Accession Number: 20153901310762
-
Record 160 of
Title:Optical design of MWIR detection system for near-space infrared detecting
Author(s):Yan, Pei-Pei(1); Liu, Kai(1); Li, Gang(1); Shan, Qiusha(1); Duan, Jing(1); Jiang, Kai(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 9676 Issue: DOI: 10.1117/12.2197895 Published: 2015
Abstract:Near-space platform has a high signal contrast and a long detection time. In order to realize effective detection of low altitude penetration target, a middle wave infrared (MWIR) optical system used in near space detection with high optical performance is given. First, the optical system scheme was described. Then on the basis of instrument and system consideration, the optical design parameters were distributed reasonably. The system had an effective focal length of 600 mm, an F-Number of F/4, a field of view of 2ω=1.16°, spatial resolution of 18 lp/mm and a working wavelength range of 3-5 μm. The system structure is simple. And the requirements of the spot, energy concentration, distortion are all satisfied. Because the change of environment temperature will deeply influence image quality of MWIR optical system, the temperature characteristic of the system is analyzed. Moreover, first-order ghost and narcissus effect of the system are all analyzed in CODEV software. The analysis results show that temperature, first-order ghost and narcissus effect requests are all satisfied. ? 2015 SPIE.
Accession Number: 20155201717462
-
Record 161 of
Title:A Robust Gradient-Based Algorithm to Correct Bias Fields of Brain MR Images
Author(s):Ling, Qiang(1); Li, Zhaohui(1); Huang, Qinghua(2); Li, Xuelong(3)
Source: IEEE Transactions on Autonomous Mental Development Volume: 7 Issue: 3 DOI: 10.1109/TAMD.2015.2416976 Published: September 2015
Abstract:We developed a novel algorithm to estimate bias fields from brain magnetic resonance (MR) images using a gradient-based method. The bias field is modeled as a multiplicative and slowly varying surface. We fit the bias field by a low-order polynomial. The polynomial's parameters are directly obtained by minimizing the sum of square errors between the gradients of MR images (both in the x-direction and y-direction) and the partial derivatives of the desired polynomial in the log domain. Compared to the existing retrospective algorithms, our algorithm combines the estimation of the gradient of the bias field and the reintegration of the obtained gradient polynomial together so that it is more robust against noise and can achieve better performance, which are demonstrated through experiments with both real and simulated brain MR images. ? 2009-2011 IEEE.
Accession Number: 20154701561388
-
Record 162 of
Title:A modified star map identification method suitable for astronomical camera
Author(s):Liu, Meiying(1); Wang, Hu(1); Wen, Desheng(1); Liu, Jie(1); Xue, Yaoke(1); Liu, Yang(1); Zhao, Hui(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 9675 Issue: DOI: 10.1117/12.2199618 Published: 2015
Abstract:High accuracy star map identification results are the basis of astronomical positioning. The traditional triangle star identification algorithm has a higher redundancy and a poor robustness to noise. Considering the specific requirements of the star map identification of the astronomical camera, in allusion to this default, proceeding with selection of guide stars, construction of guide star catalogue and realization of matching algorithm, a modified triangle algorithm based on traditional one is presented. With the proposed algorithm, the guide star is selected from astronomical durchmusterung. In order to speed up guide star indexing, the guide star catalogue is founded after dividing the sky using the overlapping rectangle method. The guide star sub-catalogue is constructed by the radius of guide triangle circumcircle and the two sides of guide triangle. The characteristic radius is used for indexing and sorted in an ascending order to improve the searching efficiency in the processing of star map identification. The matching scope of the angular distance is narrowed and the matching rate of angular distance is improved by the matching of the characteristics radius. If there exists redundancy, a normalized magnitude is used to eliminate it. Within the observing area of the real sky, the 1050 star maps continuously are calculated. The simulation results show that, the identification rate of this algorithm is greater than 97. 83% when the noise of position error is two pixels, and the average identification time is about 25. 07ms. Compared with the traditional triangle algorithm, this modified algorithm has a couple of advantages, including the smaller storage capacity of guide star catalogue, better robustness to position and magnitude error, higher rate of correcting star map identification and lower redundancy. ? 2015 SPIE.
Accession Number: 20161602266775
-
Record 163 of
Title:An efficient MRF embedded level set method for image segmentation
Author(s):Yang, Xi(1); Gao, Xinbo(1); Tao, Dacheng(2); Li, Xuelong(3); Li, Jie(4)
Source: IEEE Transactions on Image Processing Volume: 24 Issue: 1 DOI: 10.1109/TIP.2014.2372615 Published: January 1, 2015
Abstract:This paper presents a fast and robust level set method for image segmentation. To enhance the robustness against noise, we embed a Markov random field (MRF) energy function to the conventional level set energy function. This MRF energy function builds the correlation of a pixel with its neighbors and encourages them to fall into the same region. To obtain a fast implementation of the MRF embedded level set model, we explore algebraic multigrid (AMG) and sparse field method (SFM) to increase the time step and decrease the computation domain, respectively. Both AMG and SFM can be conducted in a parallel fashion, which facilitates the processing of our method for big image databases. By comparing the proposed fast and robust level set method with the standard level set method and its popular variants on noisy synthetic images, synthetic aperture radar (SAR) images, medical images, and natural images, we comprehensively demonstrate the new method is robust against various kinds of noises. In particular, the new level set method can segment an image of size 500 x 500 within 3 s on MATLAB R2010b installed in a computer with 3.30-GHz CPU and 4-GB memory. ? 2014 IEEE.
Accession Number: 20145100338437
-
Record 164 of
Title:Tracking Human Pose Using Max-Margin Markov Models
Author(s):Zhao, Lin(1); Gao, Xinbo(2); Tao, Dacheng(3); Li, Xuelong(4)
Source: IEEE Transactions on Image Processing Volume: 24 Issue: 12 DOI: 10.1109/TIP.2015.2473662 Published: December 1, 2015
Abstract:We present a new method for tracking human pose by employing max-margin Markov models. Representing a human body by part-based models, such as pictorial structure, the problem of pose tracking can be modeled by a discrete Markov random field. Considering max-margin Markov networks provide an efficient way to deal with both structured data and strong generalization guarantees, it is thus natural to learn the model parameters using the max-margin technique. Since tracking human pose needs to couple limbs in adjacent frames, the model will introduce loops and will be intractable for learning and inference. Previous work has resorted to pose estimation methods, which discard temporal information by parsing frames individually. Alternatively, approximate inference strategies have been used, which can overfit to statistics of a particular data set. Thus, the performance and generalization of these methods are limited. In this paper, we approximate the full model by introducing an ensemble of two tree-structured sub-models, Markov networks for spatial parsing and Markov chains for temporal parsing. Both models can be trained jointly using the max-margin technique, and an iterative parsing process is proposed to achieve the ensemble inference. We apply our model on three challengeable data sets, which contains highly varied and articulated poses. Comprehensive experimental results demonstrate the superior performance of our method over the state-of-the-art approaches. ? 2015 IEEE.
Accession Number: 20154201388175
-
Record 165 of
Title:Large aperture diffractive telescope design for space-based lidar receivers
Author(s):Zhu, Jinyi(1); Xie, Yongjun(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 9795 Issue: DOI: 10.1117/12.2208104 Published: 2015
Abstract:Diffractive telescopes are ideal to space-based lidar receivers, because of their advantages of mass and surface shape tolerances. To develop diffractive optical systems, the aberration properties and high order diffraction of diffractive lenses were discussed. The aberration properties are suitable for lidar receivers. High order diffraction is helpful to improve diffractive lens fabrication and decrease system length. And it can be realized by modifying the surface figures of a diffractive lens, mainly the ring widths and depth. A 1-meter aperture diffractive telescope design with simple structure was given, providing spot diameters less than 45μm over the whole field of view. ? 2015 SPIE.
Accession Number: 20161702279096
-
Record 166 of
Title:Narrow-linewidth double-peak figure-eight passively mode-locked fiber laser
Author(s):Liu, Xianglian(1); Li, Xiaohui(2,3); Zhang, Wei(2); Wang, Yishan(2)
Source: Laser Physics Volume: 25 Issue: 6 DOI: 10.1088/1054-660X/25/6/065105 Published: June 1, 2015
Abstract:We report on the experimental observation of narrow-linewidth double-peak dissipative solitons in a figure-eight Yb-doped passively mode-locked fiber laser in the large net normal cavity dispersion regime. Without any physical bandpass filters in the cavity, stable mode-locking pulses with a duration of 416 ps and a 3 dB bandwidth of 0.3 nm can be directly generated from the laser cavity. The edge-to-edge bandwidth of the spectrum is about 5 nm. The repetition rate of the dissipative solitons is 3.9 MHz. With the increase of pump power, the central wavelength of the dissipative solitons shifts toward a short wavelength and edge-to-edge spectral widths are widened gradually. These phenomena are theoretically explained. ? 2015 Astro Ltd.
Accession Number: 20152200883714
-
Record 167 of
Title:Robust Match Fusion Using Optimization
Author(s):Qin, Xiameng(1); Shen, Jianbing(1); Mao, Xiaoyang(2); Li, Xuelong(3); Jia, Yunde(1)
Source: IEEE Transactions on Cybernetics Volume: 45 Issue: 8 DOI: 10.1109/TCYB.2014.2355140 Published: August 1, 2015
Abstract:In this paper, we present a novel patch-based match and fusion algorithm by taking account of moving scene in a multiple exposure image sequence using optimization. A uniform iterative approach is developed to match and find the corresponding patches in different exposure images, which are then fused in each iteration. Our approach does not need to align the input multiple exposure images before the fusion process. Considering that the pixel values are affected by various exposure time, we design a new patch-based energy function that will be optimized to improve the matching accuracy. An efficient patch-based exposure fusion approach using the random walker algorithm is developed to preserve the moving objects from the input multiple exposure images. To the best of our knowledge, our algorithm is the first patch-based exposure fusion work to preserve the moving objects of dynamic scenes that does not need the registration process of different exposure images. Experimental results of moving scenes demonstrate that our algorithm achieves visually pleasing fusion results without ghosting artifacts, while the results produced by the state-of-the-art exposure fusion and tone mapping algorithms exhibit different levels of ghosting artifacts. ? 2013 IEEE.
Accession Number: 20153001072016
-
Record 168 of
Title:Learning a Probabilistic Topology Discovering Model for Scene Categorization
Author(s):Zhang, Luming(1); Ji, Rongrong(2); Xia, Yingjie(3); Zhang, Ying(1); Li, Xuelong(4)
Source: IEEE Transactions on Neural Networks and Learning Systems Volume: 26 Issue: 8 DOI: 10.1109/TNNLS.2014.2347398 Published: August 1, 2015
Abstract:A recent advance in scene categorization prefers a topological based modeling to capture the existence and relationships among different scene components. To that effect, local features are typically used to handle photographing variances such as occlusions and clutters. However, in many cases, the local features alone cannot well capture the scene semantics since they are extracted from tiny regions (e.g., 4 × 4 patches) within an image. In this paper, we mine a discriminative topology and a low-redundant topology from the local descriptors under a probabilistic perspective, which are further integrated into a boosting framework for scene categorization. In particular, by decomposing a scene image into basic components, a graphlet model is used to describe their spatial interactions. Accordingly, scene categorization is formulated as an intergraphlet matching problem. The above procedure is further accelerated by introducing a probabilistic based representative topology selection scheme that makes the pairwise graphlet comparison trackable despite their exponentially increasing volumes. The selected graphlets are highly discriminative and independent, characterizing the topological characteristics of scene images. A weak learner is subsequently trained for each topology, which are boosted together to jointly describe the scene image. In our experiment, the visualized graphlets demonstrate that the mined topological patterns are representative to scene categories, and our proposed method beats state-of-the-art models on five popular scene data sets. ? 2014 IEEE.
Accession Number: 20153001056581
