Starting from the application requirements of space remote sensing cameras, focusing on surface stability, researches on Carbon Fiber Reinforced Polymer (CFRP) mirror material selection, structural optimization design, substrate preparation and dimensional stability control, optic manufacture and coating had been carried out, a sample mirror with a diameter of 200 mm was successfully prepared, and passed the test of the simulated space environment, which solved the problem of the change of the surface figure of the CFRP mirror, this laid the foundation for the development of a larger diameter CFRP mirror and its early successful application in space cameras.
Cataloguing and recognition of space targets is becoming one of the important research contents of Space Situational Awareness (SSA). As is known that spectral feature is one important method for spatial targets classification and recognition. Based on the facts that objects have unique spectral distributions, characteristic spectra of objects can be used to classify and recognize objects. In order to acquire data cube of targets in both spatial and spectral dimensions by a snapshot, a hyper-spectral computing imaging technology with double channels was proposed in this paper. The imager can quickly acquire and reconstruct spectral data of space targets and then confirm the type of targets by comparing with prior spectral databases of different space targets. Sensitivity of the imager affects the longest detection distance and the spectral resolution of targets. In order to enhance its sensitivity, SPAD array with detection sensitivity to single-photon level can greatly enhance systems' performances.
Imaging spectrometer can provide both scene image information and spectral information, thus providing in-depth analysis of the composition and characteristics of the scene target. It is an important equipment for observation, analysis and detection. Imaging spectrometers are now emerging as an important market growth point in the field of optoelectronic imaging. This paper presents a compact and lightweight snapshot broadband computational spectral imager, which provides a new approach to VIS-NIR spectral imaging and target identification techniques. Based on the Coded Aperture Snapshot Spectral Imager (CASSI), an imaging method with a shared primary mirror and a dual optical path is proposed. One optical path mainly consists of a coding mask, a relay lens, an Amici prism and a visible near-infrared enhancement detector. Its spatial and spectral resolution is determined by the coding mask and dispersive elements. The optical system finally obtains a blended two-dimensional image on the detector. Another optical path uses a visible NIR-enhanced detector to provide high-resolution spatial information. The high-resolution spectral image information is obtained by a compression-aware reconstruction algorithm. Optical simulations and experimental results show that the system offers significant performance improvements over existing systems, allowing the construction of compact and sensitive spectral imaging systems. We obtained 24 spectral images in the band range 0.44-0.8μm. The new spectral imager introduced in this paper has the advantages of real-time detection, long-range monitoring and high sensitivity. It is especially suitable for Unmanned Aerial Vehicle (UAV) and NanoSat. It can be widely used in the fields of environmental remote sensing, agricultural census, forest survey, vegetation assessment and management, mineral exploration, etc.
The hyperspectral images of airplanes and flying birds are obtained by a xiSpec snapshot mosaic hyperspectral cameras, supported by the Interuniversity Microelectronics Centre (IMEC). The single frame Infrared Patch-Image (IPI) model is used to detect the small targets of airplanes and flying birds under complex cloud background in the hyperspectral images. Based on the non-local autocorrelation property of the background image, the method assumes that the target image is a sparse matrix and the background image is a low-rank matrix. The small target detection is transformed into an optimization problem of recovering the low-rank and sparse matrix. Using stable principal component tracking solution, the decomposed background and target are obtained. The results show that this method can detect bright and dark small targets in complex background at the same time, and the hyperspectral image can effectively improve the detection rate. More importantly, the detection ability is closely related to the intensity difference of the target against the background. Thus, the optimal waveband of different targets can be given by combining the target detection results and the intensity difference curves. This has a guiding significance for the design of specific point target detection payloads.
We study a super-resolution synthetic aperture imaging scheme called macroscopic fourier aperture scanning imaging. By scanning the aperture on the Fourier plane of the optical system, we get a series of low resolution images of the scene. Then, the collected images are synthesized iteratively in the frequency domain. In the initial stage of recovery, the highresolution complex wave front is recovered without any phase information. The mathematical model of the imaging system is established, and the scene super-resolution imaging and phase recovery are realized through simulation. This macroscopic fourier superposition imaging technology has broad application prospects in the fields of long-distance highresolution imaging, remote sensing detection and so on.
Spectral imaging technology can obtain a three-dimensional data cube of the target, which has the advantage of "unification of maps". Analyzing the "fingerprint" spectral information of space targets is a powerful method for space target identification. In response to the needs of space target material identification and key part identification, this paper proposes a new method of computational spectral imaging with high Light utilization for space target detection. A high-resolution spatial spectral image is obtained through the combination of panchromatic channel and calculated spectral channel. Introduce the calibration technology of the system, including the target's spectrum calibration and the system's coding calibration technology. The multi-spectral image of the satellite model taken by the new spectral imaging system is used to expand the sample, and the training set data is used for training, and the entire data set is tested. The average recognition rate of the five categories of satellite main body, windsurfing board, pot body, antenna and space background is 74.86%. If only the identification of the target and the background is considered, and the non-critical part of the satellite antenna is not considered, the probability of correct recognition as a target is 98.92%, and the probability of correct recognition as a background is 99.11%.
The conventional diffractive optical imaging spectrometer uses the single-channel scheme, it is mainly aimed at simple targets, or gas targets with known spectral characteristics. The main disadvantage of conventional system is: if the target is a complex scene such as a natural scene, it's very difficult to demodulate spectral images accurately. Because, the focused and defocused spectral information are superimposed on each other. And, the real system has noise, manufacturing error, testing error and calibration error. So, it is difficult to correctly describe the dispersion parameters of the diffractive spectrometer, which will cause large errors of spectral demodulation accuracy. To solve this problem, an efficient system of diffractive spectral imaging is discussed, which includes a reference channel. Based on the conventional single-channel system, a grayscale camera or a color camera is added for imaging. It can provide a priori knowledge of complex scenes for the diffraction imaging channel. The data of the two channels are jointly processed to improve the final demodulation accuracy of the spectral data. The system composition and basic principles are introduced, the performance of the system is analyzed. The virtual simulation experiment of diffractive optic imaging is established. The simulation of diffractive imaging and spectral demodulation of complex scene have been finished. The demodulation output images are almost the same as the original input image. The experiment system of diffractive optic imaging in visible band is also established in the laboratory. Theoretical analysis, imaging simulation and imaging experiment have verified the validity and feasibility of the diffraction imaging system with reference channel. Compared with the single channel system, the spectral demodulation effect is obviously improved, which greatly improves the application potential and application value.
Infrared imaging spectrometer can provide scene image information and spectral information at the same time, so as to deeply analyze the components and characteristics of the scene target. Due to the low resolution of the existing long-wave infrared imaging spectrometer filter and dispersion devices and the serious attenuation of signal energy, the time-modulated Fourier transform infrared spectrometer has a large volume and a high cost. In this paper, we propose a compact snapshot-type long-wave infrared computational spectral imaging method, which provides a new method for infrared spectral imaging and target recognition technology. Based on the coded aperture snapshot spectral imager (CASSI), we propose an imaging method that shares the main lens with two optical paths. One optical path is mainly composed of a coded mask, a relay lens, an amici prism, and a long-wave infrared detector. Its spatial and spectral resolution is determined by the encoded mask and the dispersive element. The optical system finally obtains an aliased two-dimensional image on the detector. The other optical path uses a long-wave infrared detector to provide high-resolution spatial information. Combining the two paths to obtain high-resolution infrared spectral image information through a compressed sensing reconstruction algorithm. The new spectroscopic imager described in this paper has the advantages of real-time detection, long-distance monitoring, and high sensitivity. It is especially suitable for mobile platforms of unmanned aerial vehicle and NanoSat. Can be widely used in trace gas detection, environmental pollution monitoring, medical diagnosis and military aircraft identification and guidance of anti-missile.
The simultaneous acquisition of spatial information, spectral information and polarimetric information can obtain more characteristic information to distinguish targets. The conventional spectral polarization imaging system mainly includes the filter/polarization wheel rotation system, the crystal modulation system and multi-path beam splitting system. The disadvantages of these systems are: unsynchronized spectral polarization detection, requiring dynamic modulation, complex system, etc. To solve these problems, a spectral polarization detection technology based on optical fiber image bundle is proposed, which combines optical fiber imaging spectral technology with pixel level polarization detection technology. The input shape of the optical fiber image bundle is plane, and the output shape is linear. Optical fiber image bundle can transform the information of array target into that of linear array. The linear array information is the input of spectral imaging system. The polarization detection uses a micron level polarization array to match the pixel size of the detector. The technology can synchronously acquire the two-dimensional spatial information, the spectral information and linear polarization information of the target. The technology can be used to image the area target in snapshot mode. The experimental device is set up to obtain the spectral image in the visible light range, as well as the polarization degree image and polarization angle image of each spectral segment. The data acquisition ability of the system is verified. With the improvement of optical fiber manufacturing technology, the integration of optical fiber is getting better, and the scale of optical fiber is getting larger. The technology will have a high application value in astronomical observation, atmospheric detection, target recognition and other fields.
Inspired by the retinal structure of elephantnose fish, bioinspired photosensitivity enhancer (BPE) with many pyramid microphotocollectors can enhance the image intensity and the imaging capability under low light conditions. To study the application of BPE on space remote sensing, this paper introduced BPE into remote sensors and analyzed several parameters such as ground sampling distance, signal, noise, signal to noise ratio and so on in normal and low light conditions and compared BPE with binning technology. The results showed that, as an optical enhancing method, BPE has better performance than binning technology. The detectability of conventional systems under low light conditions could be improved by placing BPE in front of the sensors.
Due to its advantages on the cost, power and size, the study of the CMOS image sensor is considered as an important direction of the development of low-light-level image sensor. However, the sensitivity of current CMOS image sensor does not satisfy the low-light-level application requirements. This paper introduces several key techniques on how to improve the sensitivity of CMOS image sensors. We introduce a novel CMOS low-light-level image sensor based on Geiger mode avalanche photodiode (GM-APD) and digital TDI technology. Noise characteristics and complete signal-tonoise ratio(SNR) theoretical models are constructed for both sensors. A comparison of SNR performance of two image sensors is also done by numerical simulation in this paper. The results show that the novel CMOS low-light-level image sensor outperforms EMCCD at the very low light level.
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