Backscanning step and stare imaging system with high frame rate and wide coverage

Sun, Chongshang; Ding, Yalin; Wang, Dejiang; Tian, Dapeng

doi:10.1364/ao.54.004960

Cited by 29 publications

(17 citation statements)

References 12 publications

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“…In this paper the slanted edge method is used to provide a fast and effective MTF measurement [12]. The slanted edge method has been used to measure MTF on orbit and modified methods have been proposed to improve the measuring accuracy [13][14][15]. For the sake of increasing the sampling frequency and eliminating the aliasing effect, the knife-edge is slightly slanted compared with the knife-edge method.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Modulation Transfer Function Analysis of Images Blurred by Sinusoidal Vibration

Ding

et al. 2016

Journal of the Optical Society of Korea

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The dynamic modulation transfer function (MTF) for image degradation caused by sinusoidal vibration is formulated based on a Bessel function of the first kind. The presented method makes it possible to obtain an analytical MTF expression derived for arbitrary frequency sinusoidal vibration. The error obtained by the use of finite order sum approximations instead of infinite sums is investigated in detail. Dynamic MTF exhibits a stronger random behavior for low frequency vibration than high frequency vibration. The calculated MTFs agree well with the measured MTFs with the slant edge method in imaging experiments. With the proposed formula, allowable amplitudes of any frequency vibration are easily calculated. This is practical for the analysis and design of the line-of-sight stabilization system in the remote sensing camera.

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Section: Methodsmentioning

confidence: 99%

Dynamic Modulation Transfer Function Analysis of Images Blurred by Sinusoidal Vibration

Ding

et al. 2016

Journal of the Optical Society of Korea

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“…With the development of aerial photoelectric loads, such as airborne cameras and photoelectric pods, long-distance oblique imaging has become a major method for obtaining aerial remote sensing images. Unlike overlooking imaging, oblique imaging can better describe specific details of urban buildings, which is conducive to 3D modeling, map marking, and other works [4]. To achieve these goals, a high-accuracy geo-location of urban building targets should be realized.…”

Section: Introductionmentioning

confidence: 99%

Geo-Location Algorithm for Building Targets in Oblique Remote Sensing Images Based on Deep Learning and Height Estimation

et al. 2020

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To improve the accuracy of the geographic positioning of a single aerial remote sensing image, the height information of a building in the image must be considered. Oblique remote sensing images are essentially two-dimensional images and produce a large positioning error if a traditional positioning algorithm is used to locate the building directly. To address this problem, this study uses a convolutional neural network to automatically detect the location of buildings in remote sensing images. Moreover, it optimizes an automatic building recognition algorithm for oblique aerial remote sensing images based on You Only Look Once V4 (YOLO V4). This study also proposes a positioning algorithm for the building target, which uses the imaging angle to estimate the height of a building, and combines the spatial coordinate transformation matrix to calculate high-accuracy geo-location of target buildings. Simulation analysis shows that the traditional positioning algorithm inevitably leads to large errors in the positioning of building targets. When the target height is 50 m and the imaging angle is 70°, the positioning error is 114.89 m. Flight tests show that the algorithm established in this study can improve the positioning accuracy of building targets by approximately 20%–50% depending on the difference in target height.

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“…Modern intelligence, surveillance, and reconnaissance systems strongly require to have wide area coverage and high-resolution imaging abilities. High-resolution imaging has often been achieved at the cost of a small field of view (FOV) for current electro-optical and infrared sensors [1]. In certain imaging applications, such as infrared search and track (IRST) systems, it is desirable for the imaging sensor to scan large fields of regard at a high rate and with diffraction limited performance.…”

Section: Introductionmentioning

confidence: 99%

Non-Rotationally Symmetric Field Mapping for Back-Scanned Step/Stare Imaging System

Xin

Zhang

et al. 2020

Applied Sciences

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Step/stare imaging with focal plane arrays (FPAs) has become the main approach to achieve wide area coverage and high resolution imaging for long range targets. A fast steering mirror (FSM) is usually utilized to provide back-scanned motion to compensate for the image motion. However, the traditional optical design can just hold one field point relatively stable, typically the central or on-axis field point, on the FPA during back-scanning; all other field points may wander during the exposure due to imaging distortion characteristics of the optical system, which reduces the signal to noise ratio (SNR) of the target. Aiming toward this problem, this paper proposes a non-rotationally symmetric field mapping method for the back-scanned step/stare imaging system, which can make all field points stable on the FPA during back-scanning. First of all, the mathematical model of non-rotationally symmetric field mapping between object space and image space is established. Then, a back-scanned step/stare imaging system based on the model is designed, in which this non-rotationally symmetric mapping can be implemented with an afocal telescope including freeform lenses. Freeform lenses can produce an anamorphic aberration to adjust distortion characteristics of the optical system to control image wander on an FPA. Furthermore, the simulations verify the effectiveness of the method.

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Backscanning step and stare imaging system with high frame rate and wide coverage

Cited by 29 publications

References 12 publications

Dynamic Modulation Transfer Function Analysis of Images Blurred by Sinusoidal Vibration

Dynamic Modulation Transfer Function Analysis of Images Blurred by Sinusoidal Vibration

Geo-Location Algorithm for Building Targets in Oblique Remote Sensing Images Based on Deep Learning and Height Estimation

Non-Rotationally Symmetric Field Mapping for Back-Scanned Step/Stare Imaging System

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