Analytical method for calculating internal stray radiation from an IR spectrometer based on the view factor.

Optomechanical components such as the lens barrels and frames of IR spectrometers produce strong internal stray radiation, which reduces the instrument's SNR and dynamic range. An IR internal stray radiation calculation method based on an analytical model of the view factor is proposed. The mathematical model of the view factor calculation method of typical optomechanical components is established. For any IR optical systems, the internal stray radiation can be quickly and accurately calculated by adjusting the coordinate systems in the calculation method. Based on the proposed method, the internal stray radiation of a double-pass long-wave IR spectrometer was calculated. The calculation results are consistent with the simulation results. The RMS value of the relative error between the calculated value and the simulated value is around 11%. To verify the proposed method, an experiment was conducted to test the internal stray radiation of the long-wave IR spectrometer. The internal stray radiation test results agree with the calculated and simulated results, and the relative error between the test results and the calculation results is within 9%.

Comprehensive design analysis and verification of space-based short-wave infrared coded spectrometer via curved prism dispersion.

The spaceborne dispersive spectrometer is widely used in environmental, resource, and ocean observations. The coded spectrometer has higher energy advantages than the dispersion spectrometer, so it has great application prospects. In the current study, we developed an off-axis short-wave infrared coded optical system (SICOS) based on curved prism dispersion, and we further explored the design and optimization of the SICOS structure. Finite element analyses of a space-based short-wave infrared coded spectrometer based on curved prism dispersion (SSICS-CPD), including static simulation, modal analysis, sinusoidal vibration mechanical analysis, and random vibration mechanical analysis, were carried out. Simulation results showed that the SICOS support structure had excellent mechanical and thermal stability. As off-axis optical systems cannot meet the requirements of optical position accuracy through centering processing, a point source microscope and three-coordinate measuring machines were employed to complete the high-precision and rapid assembly of the SSICS-CPD. In addition, verification tests of surface shape error, stress relief, random vibration, and optical design parameters were carried out to validate the high stability and imaging performance of the SSICS-CPD. Results showed that the average modulation transfer function in the full field was 0.43 at 16.67 lp/mm, the spectral smile was <0.2 pixels, and the spectral keystone was <0.1 pixels. The design, analysis, assembly, and verification of the SSICS-CPD provide a useful reference for the development of other spaceborne prism dispersion spectrometers.

Design analysis and test verification of a rigid-flexible, dual-mode coupling support structure for space-based rectangular curved prisms.

In view of the functional requirements of high reliability and stability support of optical components of space remote sensors, a rigid-flexible, dual-mode coupling support structure for space-based rectangular curved prisms (SRCPs) was designed. In-depth studies of the support principle and engineering realization of the SRCPs and optimization of the flexible adhesive structure were performed. Static and dynamic simulations were conducted on the mirror subassembly by means of finite element analysis, and test verification was also performed. The tests revealed that the surface shape error of the mirror subassembly after mechanical testing was 0.021λ, the displacement of the mirror body was 0.008 mm, the inclination angle was ∼0.8'', the mass of the mirror subassembly was 4.79 kg, the fundamental frequency was 283 Hz, and the maximum amplification of the total rms acceleration was 4.37. All indexes were superior to those of the design requirements. On this basis, bonding tests and mechanical tests of a rectangular curved prism reflector, a rectangular curved prism, and a rectangular plane reflector employing this proposed support structure were continued. The test results verified the reliability, stability, and universal applicability of the proposed rigid-flexible, dual-mode peripheral bonding support structure.

A Review of Functional Near-Infrared Spectroscopy Studies of Motor and Cognitive Function in Preterm Infants.

Preterm infants are vulnerable to brain injuries, and have a greater chance of experiencing neurodevelopmental disorders throughout development. Early screening for motor and cognitive functions is critical to assessing the developmental trajectory in preterm infants, especially those who may have motor or cognitive deficits. The brain imaging technology functional near-infrared spectroscopy (fNIRS) is a portable and low-cost method of assessing cerebral hemodynamics, making it suitable for large-scale use even in remote and underdeveloped areas. In this article, we review peer-reviewed, scientific fNIRS studies of motor performance, speech perception, and facial recognition in preterm infants. fNIRS provides a link between hemodynamic activity and the development of brain functions in preterm infants. Research using fNIRS has shown different patterns of hemoglobin change during some behavioral tasks in early infancy. fNIRS helps to promote our understanding of the developmental mechanisms of brain function in preterm infants when performing motor or cognitive tasks in a less-restricted environment.

[A Novel Spatial-Spectral Sparse Representation for Hyperspectral Image Classification Based on Neighborhood Segmentation].

Traditional hyperspectral image classification algorithms focus on spectral information application, however, with the increase of spatial resolution of hyperspectral remote sensing images, hyperspectral imaging presents clustering properties on spatial domain for the same category. It is critical for hyperspectral image classification algorithms to use spatial information in order to improve the classification accuracy. However, the marginal differences of different categories display more obviously. If it is introduced directly into the spatial-spectral sparse representation for image classification without the selection of neighborhood pixels, the classification error and the computation time will increase. This paper presents a spatial-spectral joint sparse representation classification algorithm based on neighborhood segmentation. The algorithm calculates the similarity with spectral angel in order to choose proper neighborhood pixel into spatial-spectral joint sparse representation model. With simultaneous subspace pursuit and simultaneous orthogonal matching pursuit to solve the model, the classification is determined by computing the minimum reconstruction error between testing samples and training pixels. Two typical hyperspectral images from AVIRIS and ROSIS are chosen for simulation experiment and results display that the classification accuracy of two images both improves as neighborhood segmentation threshold increasing. It concludes that neighborhood segmentation is necessary for joint sparse representation classification.

[A New Spectral-Spatial Algorithm Method for Hyperspectral Image Target Detection].

With high-resolution spatial information and continuous spectrum information, hyperspectral remote sensing image -has a unique advantage in the field of target detection. Traditional hyperspectral remote sensing image target detection methods emphasis on using spectral information to determine deterministic algorithm and statistical algorithms. Deterministic algorithms find the target by calculating the distance between the target spectrum and detected spectrum however, they are unable to detect sub-pixel target and are easily affected by noise. Statistical methods which calculate background statistical characteristics to detect abnormal point as target. It can detect subpixel target targets and small targets better thanbig size target,. With the spatial resolution increasing, subpixel target detection target has gradually grown to a single pixel and multi-pixel target. At this point, hyperspectral image usually has large homogeneous regions where the neighboring pixels wihin the regions consist of the same type of materials and have a similar spectral characteristics, therefore, the spatial information should be needed to incorporate into the algorithm for targe detection. This paper proposes an algorithm for hyperspectral target detection combined spectrum characteristics and spatial characteristics. The algorithm is based on traditional target detection operator and combined neighborhood clustering statistics. Firstly, the algorithm uses target detection operator to divided hyperspectral image into a potential target region and background region. Then, it calculates the centroid of the potential target area. Finally, as the centroid for neighborhood clustering center to clust data in order to exclud background from potential target area, through iterative calculation to obtain the final results of the target detection. The traditional statistics algorithms defines the total image as background area in order to extract background statistics features, and the algorithm propsed devided the total image into background part and potential target part, which cut off the target interference for background statistics feature extraction. Compared with CEM operators and ACE operators, the algorithm proposed outperforms than traditional operators in big target detection .

[Coded aperture spectral data restoration based on two-step iterative shrinkage/threshold].

Coded aperture imaging spectrometer based on the concept of compressed sensing can acquire the spectral diagram of object. Coded aperture spectral data restoration reconstructs three-dimensional data cube from two-dimensional coded image. The two-step iterative shrinkage/thresholding algorithms were derived from the iterative shrinkage threshold algorithm and weighted iterative shrinkage algorithm. Recovering coded aperture spectral data using the two-step iterative shrinkage/thresholding algorithms obtained the three-dimensional spectral data cube successfully.

[Design of airborne dual channel ultraviolet-visible imaging spectrometer with large field of view, wide spectrum, and high resolution].

The ultraviolet-visible (UV-Vis 200-500 nm) imaging spectrometer is an important part of space remote sensing. Based on special requirements and practical application of the airborne UV-VIS spectrometer, a kind of scanning imaging spectrometer using area array CCD is proposed, which can meet the application requirements of large field of view, wide spectrum and high resolution. It overcomes low spatial resolution of traditional line array CCD scanning imaging spectrometer, and limited field of view of the pushbroom imaging spectrometer. In addition, dual channel was designed to reduce stray light. 400-500 nm band includes two order spectrum for 200-250 nm band, and variation of radiance from earth between the shorter wavelength (<290 nm) and the longer wavelength (>310 nm) is above three orders of magnitude. In the structure design of the system, the imaging spectrometer is composed of a two-mirror concentric telescope and two Czerny-Turner plane grating imaging spectrometers. The whole system doesn't use any additional optical elements in addition to spherical mirrors. The whole system has the advantage of simple structure, excellent performance, and very good feasibility. The modulation transfer function value of full spectrum and full field of view is above 0.6.

[Design and implementation of real-time processing platform for movement error correction of hyperspectrual imaging].

The approach that deals with compressed and packed image data transmitted from satellite to the ground is too slow for real-time application occasion, it also has huge image, multi-processing step and complexity recovery arithmetic synchronously, so it is urgent to build accurate and fast data processing platform for real-time processing. For the moment, the platform for data recovery and error correction is much less, the so-called successful platform may directly affect the effect of target detection and identification because of processing speed, precision, flexibility, configuration and upgrade. The platform we build is to set spatial modulation spectrometer as the research goal, We design and implement a hardware platform based on Xilinx Virtex-5 FPGA, It is combined with ISE IP soft-core resources which is configurable, high-precision and flexible by focusing on analyzing key aspects of the hardware platform. And the relevant test data were drawn, then a good way for spectrum recovery and error correction was explored.

[The melioration on spectra response heterogeneity of hadamard transform spectral imager].

Hadamard transform optics has been developed in the past decades. It has been used in distinguishing targets, detecting feeble signals and so on. Hadamard transform spectral imager (HTSI), based on digital micro-mirror device, is a new dispersion spectral imager. HTSI has been developed in our laboratory. The spectral heterogeneity of encoded image captured by HTSI has been researched according to spectrum calibration in this paper. Relative and absolute spectrum emittance calibration algorithms have been proposed first time on HTSI to meliorate the spectrum heterogeneity. It aims at the problem that the accuracy of recovered spectrum is depressed by the heterogeneity noise and disorder encoding spectrum in spectral image. Simulation and experiment result have demonstrated that the meliorated spectral curve is close to the standard spectrum, and the variance of the recovered spectrum ranges from 2.4% to 4.2% with regard to the spectral image of 7 waves. This is fully satisfied for the requirement of laboratory and projects.

[Research on the interlaced encoding pixels in Hadamard transform spectral imager based on DMD].

The key innovation in Hadamard transform spectral imager (HTSI) introduced recently is the use of digital micro-mirror device (DMD) to encode spectral information. However, it brings some new problems for us to solve synchronously. An interlaced encoding phenomenon caused by the application of DMD to our HTSI was investigated and analyzed. These interlaced encoding pixels were not encoded based on Hadamard transform; therefore they should be processed specially in spectrum recovery. To improve the quality of the recovered spectral images, a positioning method and a decoding method for the interlaced encoding pixels were proposed. In our experiment, we first directed a beam of laser into our HTSI to fill the field of view and labeled the positions of the interlaced encoding pixels. Then we recorded two groups of the encoded images of the target by changing the positions of all the encoding channels on the DMD. The interlaced encoding pixels could be distinguished easily by observing the number of non-zero constants and zero elements in a column vector which is made up of the gray values of a pixel of the encoded images in sequence. The interlaced encoding pixels of the first group of the encoded images turned into the normal Hadamard encoding pixels of the second group of the encoded images. The interlaced encoding pixels of the first group of the encoded images can be decoded through applying inverse Hadamard transform to the corresponding pixels of the second group of the encoded images. The experimental results prove the feasibility of the decoding method.

[Spatial domain display for interference image dataset].

The requirements of imaging interferometer visualization is imminent for the user of image interpretation and information extraction. However, the conventional researches on visualization only focus on the spectral image dataset in spectral domain. Hence, the quick show of interference spectral image dataset display is one of the nodes in interference image processing. The conventional visualization of interference dataset chooses classical spectral image dataset display method after Fourier transformation. In the present paper, the problem of quick view of interferometer imager in image domain is addressed and the algorithm is proposed which simplifies the matter. The Fourier transformation is an obstacle since its computation time is very large and the complexion would be even deteriorated with the size of dataset increasing. The algorithm proposed, named interference weighted envelopes, makes the dataset divorced from transformation. The authors choose three interference weighted envelopes respectively based on the Fourier transformation, features of interference data and human visual system. After comparing the proposed with the conventional methods, the results show the huge difference in display time.

[Hadamard transform spectrometer mixed pixels' unmixing method].

Hadamard transform imaging spectrometer is a multi-channel digital transform spectrometer detection technology, this paper based on digital micromirror array device (DMD) of the Hadamard transform spectrometer working principle and instrument structure, obtained by the imaging sensor mixed pixel were analyzed, theory derived the solution of pixel aliasing hybrid method, simulation results show that the method is simple and effective to improve the accuracy of mixed pixel spectrum more than 10% recovery.