The Soft X-ray Imager(SXI)on the SMILE Mission

The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

Design and performance evaluation of a large field-of-view dual-particle time-encoded imager based on a depth-of-interaction detector

Time-encoded imaging is useful for identifying potential special nuclear materials and other radioactive sources at a distance.In this study,a large field-of-view time-encoded imager was developed for gamma-ray and neutron source hotspot imaging based on a depth-of-interaction(DOI)detector.The imager primarily consists of a DOI detector system and a rotary dual-layer cylindrical coded mask.An EJ276 plastic scintillator coupled with two SiPMs was designed as the DOI detector to increase the field of view and improve the imager performance.The difference in signal time at both ends and the log of the signal amplitude ratio were used to calculate the interaction position resolution.The position resolution of the DOI detector was calibrated using a collimated Cs-137 source,and the full width at half maximum of the reconstruction position of the Gaussian fitting curve was approximately 4.4 cm.The DOI detector can be arbitrarily divided into several units to independently reconstruct the source distribution images.The unit length was optimized via Am-Be source-location experiments.A multidetector filtering method is proposed for image denoising.This method can effectively reduce image noise caused by poor DOI detector position resolution.The vertical field of view of the imager was(-55°,55°)when the detector was placed in the center of the coded mask.A DT neutron source at 20 m standoff could be located within 2400 s with an angular resolution of 3.5°.

Simulation of the SMILE Soft X-ray Imager response to a southward interplanetary magnetic field turning

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.

End-to-end computational design for an EUV solar corona multispectral imager with stray light suppression

An extreme ultraviolet solar corona multispectral imager can allow direct observation of high temperature coronal plasma,which is related to solar flares,coronal mass ejections and other significant coronal activities.This manuscript proposes a novel end-to-end computational design method for an extreme ultraviolet(EUV)solar corona multispectral imager operating at wavelengths near 100 nm,including a stray light suppression design and computational image recovery.To suppress the strong stray light from the solar disk,an outer opto-mechanical structure is designed to protect the imaging component of the system.Considering the low reflectivity(less than 70%)and strong-scattering(roughness)of existing extreme ultraviolet optical elements,the imaging component comprises only a primary mirror and a curved grating.A Lyot aperture is used to further suppress any residual stray light.Finally,a deep learning computational imaging method is used to correct the individual multi-wavelength images from the original recorded multi-slit data.In results and data,this can achieve a far-field angular resolution below 7",and spectral resolution below 0.05 nm.The field of view is±3 R_(☉)along the multi-slit moving direction,where R☉represents the radius of the solar disk.The ratio of the corona's stray light intensity to the solar center's irradiation intensity is less than 10-6 at the circle of 1.3 R_(☉).

Transformer-Based Cloud Detection Method for High-Resolution Remote Sensing Imagery

Cloud detection from satellite and drone imagery is crucial for applications such as weather forecasting and environmentalmonitoring.Addressing the limitations of conventional convolutional neural networks,we propose an innovative transformer-based method.This method leverages transformers,which are adept at processing data sequences,to enhance cloud detection accuracy.Additionally,we introduce a Cyclic Refinement Architecture that improves the resolution and quality of feature extraction,thereby aiding in the retention of critical details often lost during cloud detection.Our extensive experimental validation shows that our approach significantly outperforms established models,excelling in high-resolution feature extraction and precise cloud segmentation.By integrating Positional Visual Transformers(PVT)with this architecture,our method advances high-resolution feature delineation and segmentation accuracy.Ultimately,our research offers a novel perspective for surmounting traditional challenges in cloud detection and contributes to the advancement of precise and dependable image analysis across various domains.

ZY1-02DAHSI影像归一化阴影植被指数NSVI的波段选择及其构建

高光谱影像具有连续的地物光谱信息,在阴影检测方面具有巨大的潜力,而波段冗余度高需进行波段优选。归一化阴影植被指数(NSVI)能够扩大光谱差异,在高光谱影像中应用NSVI将更有效地识别阴影。资源一号02D卫星是我国首颗自主研发并成功运行的高光谱业务卫星,数据信噪比大、覆盖能力强,对该高光谱影像进行准确的阴影检测具有重要意义。以ZY1-02DAHSI影像为试验数据,提取并分析明亮区植被、阴影区植被及水体的光谱反射率;结合竞争自适应重加权采样(CARS)和连续投影算法(SPA)筛选能够有效区分典型地物的主要波段,综合考虑算法的特性进一步选出特征波段构建NSVI;通过步长法确定最佳阈值对影像进行分类,从像元值分布情况、分类精度和光谱增强效果等对比出构建NSVI的最佳波段,并结合不同的阴影指数、波段和影像进行综合评价,验证该方法的意义及普适性。结果表明:波段32和波段73是构建NSVI的最佳波段,分别对应红光波段和近红外波段;不同波段构建的NSVI分类精度均高于90%,由最佳波段构建的NSVI分类精度为94.33%,Kappa系数为0.8328,分类效果最优;NSVI能够增强典型地物间的光谱差异并缓解归一化植被指数的“易饱和”现象,在该影像中因水体累积产生的小波峰有助于提取水体;在ZY1-02DAHSI影像中NSVI的分类效果优于归一化阴影指数和阴影指数,于另一景影像的分类精度也达到93.55%,Kappa系数为0.8167。由算法筛选出的波段具有一定的代表性,最佳波段构建的NSVI在ZY1-02DAHSI影像中具有较好的阴影检测能力,对高光谱影像阴影检测及构建植被指数具有一定的借鉴和参考意义。

Contribution of Imagery in the Diagnosis of Multisystemic Sarcoidosis in the Service Radiology Department of the Mother and Child Hospital “Le Luxembourg” in Bamako: A Case Report

The aim of this study was to report a case of multi-visceral sarcoidosis at the Mother-Child Hospital Center (CHME) “Le Luxembourg” in Bamako, Mali. Observation: This is a patient aged 62 at the time of consultation, a housewife, residing in the Banconi district, who was referred to us for thoracic-abdominopelvic imaging for chronic liver disease. After several diagnostic errors, the thoracic-abdominopelvic CT scan and liver MRI performed in our center showed, at the thoracoabdominal level, bilateral diffuse pulmonary micronodules and bilateral mediastinal-hilar lymphadenopathy;on the abdominal level, a dysmorphic liver with plaques of steatosis and a granular appearance of the liver parenchyma without periportal fibrosis. These imaging data combined with those from the liver nodule biopsy and biology confirmed the diagnosis of sarcoidosis type II. Treatment with corticosteroids gave satisfactory results and the patient recovered after 18 months. Clinical and CT monitoring 2 years from the start of the disease and 2 months from the end of treatment showed complete resolution of the lesions. Conclusion: The multi-visceral location of sarcoidosis is an entity whose diagnosis remains difficult;diagnostic and interventional imaging has an important place in its management.

Lossless Compression Method for the Magnetic and Helioseismic Imager(MHI)Payload

The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.

HSI色系下的国画颜色再现技术研究

为实现国画作品的数字化重建,提出一套HSI色系下的国画颜色再现方案。基于国画材质反射特性对颜色信息特性加以分析,发现在实际操作中可以采用亮度匹配的方式实现国画作品的数字化再现,最后针对该颜色再现方法进行对比实验。经实验研究发现,所提出的国画颜色再现技术能够实现较高精度的色彩重建,重建效果十分接近拍摄效果。

基于HSI彩色模型远程测量青年男体围度拟合

为实现人体远程测量系统的有效性,提出运用人体照片来预测青年男体的围度。通过HSI颜色空间转换、轮廓光滑处理等图像处理方法提取了人体轮廓。通过识别人体特征点,得到人体的体表角度、宽度和厚度;按照体表角度、厚度/宽度等指标进行人体体型分类。基于各个围度对应的厚度和宽度构建了颈围、胸围、腰围、腹围、臀围和大腿根围的围度拟合方程,并对拟合方程进行了误差分析。结果表明,建立的围度预测模型有效,保证了人体远程测量系统的可靠性。

基于融合MaxEnt和HSI模型的驼鹿生境适宜性评价

驼鹿是国家一级保护野生动物,研究驼鹿生境适宜性是保护驼鹿种群的关键内容。以黑龙江南瓮河国家级自然保护区为对象,结合最大熵(MaxEnt)模型和生境适宜性指数(HSI)模型对驼鹿生境适宜性进行评价,利用无人机样带调查得到驼鹿分布点数据,采用MaxEnt模型得到各环境因子贡献度情况和单一环境变量响应曲线,结合保护区自然地理情况,再构建不同环境因子对驼鹿影响程度的评价模型,定量评价保护区驼鹿生境适宜性。结果表明,该区域影响驼鹿生境分布的主要环境因子是海拔(20.3%)、坡度(11.4%)、距河流距离(11.3%),而坡向、坡位、植被覆盖度对于驼鹿生境影响较小;驼鹿偏好在低海拔、坡度缓和、阳坡、靠近河流、远离人为干扰、覆盖度高的森林区域活动。在保护区内,驼鹿高适宜生境区域面积为424.6 km^(2),占保护区总面积的18.5%;低适宜生境区域面积为1422.9 km^(2),占保护区总面积的62.0%;不适宜生境区域面积为447.5 km^(2),占保护区总面积的19.5%。

基于HSI色彩空间和分水岭算法的冰雹特征参数测量

为了促进冰雹灾害等级评估工作的高效进行,提出一种测量冰雹特征参数的方法。该方法统计冰雹图片的HSI颜色范围,用先验的颜色范围来分割出冰雹并通过形态学滤除噪声,针对冰雹颗粒粘连情况运用基于分水岭算法分割边界。分别采用统计像素法、Freeman链码和改进的最小外接矩形法来测量冰雹颗粒的面积、周长和直径并与相关算法进行了实验比较。实验结果表明该方法精准度高、相关性较好,冰雹周长、面积和直径的均方根误差(Root Mean Square Error,RMSE)分别为0.2081 cm、0.2124 cm 2和0.9314 cm,决定系数(R 2)分别为0.8814、0.8736和0.9314,测量值平均误差在2%~6%之间。研究结果可为冰雹灾害相关的研究者提供准确的数据参考。

Construction and Validation of a Geometry-based Mathematical Model for the Hard X-Ray Imager

Quantitative and analytical analysis of the modulation process of the collimator is a great challenge,and is also of great value to the design and development of Fourier transform imaging telescopes.The Hard X-ray Imager(HXI),as one of the three payloads onboard the Advanced Space-based Solar Observatory(ASO-S) mission,adopts modulating Fourier-Transformation imaging technique and will be used to explore the mechanism of energy release and transmission in solar flare activities.As an important step to reconstruct the images of solar flares,accurate modulation functions of HXI are needed.In this paper,a mathematical model is developed to analyze the modulation function under a simplified condition first.Then its behavior under six degrees of freedom is calculated after adding the rotation matrix and translation change to the model.In addition,unparalleled light and extended sources are also considered so that our model can be used to analyze the X-ray beam experiment.Next,applied to the practical HXI conditions,the model has been confirmed not only by Geant4 simulations but also by some verification experiments.Furthermore,how this model helps to improve the image reconstruction process after the launch of ASO-S is also presented.

基于HSI颜色特征的变电站压板状态识别方法

针对当前变电站压板状态识别存在未充分考虑复杂光照因素以及在图像分割过程中未考虑连通域粘连的问题,提出了一种基于HSI(色调-饱和度-亮度)颜色特征和图像处理技术的压板状态识别方法。首先对采集的压板图像进行畸变矫正预处理;接着利用HSI颜色特征提取技术对图像进行分割处理;然后对连通域进行形态特征分析,利用连通域的边界信息去除标识牌,并利用极限腐蚀算法实现粘连连通域的分离;最后基于简单最小外接矩形边界特征与面积最小外接矩形的偏转角度特征融合识别压板状态。通过与传统RGB(三原色)颜色分割方法、单一长宽比识别方法进行对比试验,结果表明该方法在识别率上有较大提升,具有一定的工程应用价值。

基于HSI颜色空间暗通道的亮度保真去雾方法

图像块和像素先验是实现图像去雾的两类重要策略,但图像去雾后往往会出现亮度损失、过饱和或颜色失真等现象。本文提出了一种基于HSI颜色空间暗通道的亮度保真去雾方法,将RGB颜色空间中传统暗通道模型拓展到HSI颜色空间,以图像亮度、饱和度、颜色浓度和亮度变化构造融合图像块和像素两种先验策略的暗通道模型。通过引入颜色浓度、亮度变化与透射率的两个线性关系,构造出透射率、颜色浓度、亮度变化的方程组,增加了物理散射成像模型参数的可靠性,提高了图像透射率的精度。此外,人造和自然雾天图像去雾实验结果表明,本文方法不但保持了传统暗通道去雾的原有优势,同时也实现了对亮度和饱和度的保真,使复原结果更加逼近真实场景,也更加符合视觉感知。

Assessment of Cork Oak Decline Using Digital Multispectral Imagery in Relation with in Situ Crown Condition

Cork oak in Maamora forest is experiencing the dieback phenomenon. The evaluation of the latter in this forest has gained the importance over time and with the solicitation of managers to objectify its phytosanitary situation. Aiming at prioritizing management actions, remote sensing seems to be an effective tool to inquire about stands’ health conditions and their evolution. To this end, this study aims at mapping and validating health status of cork oak stands in Maamora. Sentinel 2 images in 2015 and 2020 were processed to calculate the differential normalized difference water index (NDWI), revealing vegetation moisture variation caused by drought. A statistical method based on thresholds was used to map cork oak dieback stands, those with no changes and those recovered. Results have shown that 54.63% of cork oak in Maamora forest have not changed in terms of phytosanitary situation between 2015 and 2020, 31.10% of oak stands are afflicted by a slight decline and 12.97% by a severe decline. Areas with slight or strong recovery remain minimal and represent 1.04% and 0.25% respectively. Ground data indicated that the map generated displayed a good distinction between stands severely and slightly declined with a global accuracy of 66.66%. Therefore, further research elaborating an advanced vegetation index reflecting the various factors of dieback would be of much importance.

Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques

The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.

Exploring the spatiotemporal relationship between green infrastructure and urban heat island under multi‐source remote sensing imagery:A case study of Fuzhou City

Green Infrastructure(GI)has garnered increasing attention from various regions due to its potential to mitigate urban heat island(UHI),which has been exacerbated by global climate change.This study focuses on the central area of Fuzhou city,one of the“furnace”cities,and aims to explore the correlation between the GI pattern and land surface temperature(LST)in the spring and autumn seasons.The research adopts a multiscale approach,starting from the urban scale and using urban geographic spatial characteristics,multispectral remote sensing data,and morphological spatial pattern analysis(MSPA).Significant MSPA elements were tested and combined with LST to conduct a geographic weighted regression(GWR)experiment.The findings reveal that the UHI in the central area of Fuzhou city has a spatial characteristic of“high temperature in the middle and low temperature around,”which is coupled with a“central scattered and peripheral concentrated”distribution of GI.This suggests that remote sensing data can effectively be utilised for UHI inversion.Additionally,the study finds that the complexity of GI,whether from the perspective of the overall GI pattern or the classification study based on the proportion of the core area,has an impact on the alleviation of UHI in both seasons.In conclusion,this study underscores the importance of a reasonable layout of urban green infrastructure for mitigating UHI.

An Effective Machine-Learning Based Feature Extraction/Recognition Model for Fetal Heart Defect Detection from 2D Ultrasonic Imageries

Congenital heart defect,accounting for about 30%of congenital defects,is the most common one.Data shows that congenital heart defects have seriously affected the birth rate of healthy newborns.In Fetal andNeonatal Cardiology,medical imaging technology(2D ultrasonic,MRI)has been proved to be helpful to detect congenital defects of the fetal heart and assists sonographers in prenatal diagnosis.It is a highly complex task to recognize 2D fetal heart ultrasonic standard plane(FHUSP)manually.Compared withmanual identification,automatic identification through artificial intelligence can save a lot of time,ensure the efficiency of diagnosis,and improve the accuracy of diagnosis.In this study,a feature extraction method based on texture features(Local Binary Pattern LBP and Histogram of Oriented Gradient HOG)and combined with Bag of Words(BOW)model is carried out,and then feature fusion is performed.Finally,it adopts Support VectorMachine(SVM)to realize automatic recognition and classification of FHUSP.The data includes 788 standard plane data sets and 448 normal and abnormal plane data sets.Compared with some other methods and the single method model,the classification accuracy of our model has been obviously improved,with the highest accuracy reaching 87.35%.Similarly,we also verify the performance of the model in normal and abnormal planes,and the average accuracy in classifying abnormal and normal planes is 84.92%.The experimental results show that thismethod can effectively classify and predict different FHUSP and can provide certain assistance for sonographers to diagnose fetal congenital heart disease.