雙清一號(珞珈三號01星)多模式成像樣例數(shù)據(jù)集
doi: 10.11999/JEIT230921
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武漢大學(xué)測繪遙感信息工程國家重點實驗室 武漢 430079
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航天東方紅衛(wèi)星有限公司 北京 100094
ShuangQing-1 (Luojia3-01) Multimode Imaging Sample Dataset
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State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
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DFH Satellite Co., Ltd., Beijing100094, China
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摘要: 針對當(dāng)前多數(shù)高分辨遙感衛(wèi)星面向用戶服務(wù)存在獲取數(shù)據(jù)種類單一問題,該文公開了雙清一號(珞珈三號01星)多模式成像樣例數(shù)據(jù)集,涵蓋了面陣推掃、面陣推幀和視頻凝視等多種成像模式,包含城市、水體、山區(qū)、機(jī)場等不同目標(biāo)區(qū)域的典型數(shù)據(jù)樣本。該數(shù)據(jù)集由信號數(shù)據(jù)解碼、Bayer插值、相對輻射校正、幾何定位、視頻穩(wěn)像和3維重建等步驟處理構(gòu)建;同時,對在軌定標(biāo)、興趣區(qū)產(chǎn)品快速生產(chǎn)、高清視頻幾何穩(wěn)像和多角度3維重建等關(guān)鍵算法做了深入探討和研究。最后,對樣本數(shù)據(jù)集從圖像標(biāo)準(zhǔn)產(chǎn)品、凝視視頻產(chǎn)品和實景3維產(chǎn)品等3個方面進(jìn)行了可視化展示和定量化精度評價。Abstract: Herein, the Shuangqing-1(Luojia3-01) multimode imaging sample dataset is presented to address the problem of limited data types provided for user services by remote sensing satellites with the highest resolution. This dataset includes various imaging modes, such as push-scan, array push-frame, and video staring; hence, it covers typical data samples from different target areas ,such as urban regions, water bodies, mountainous regions, and airports. The construction of this dataset involves signal data decoding, Bayer interpolation, relative radiometric correction, geometric positioning, video stabilization, and three-dimensional reconstruction. Additionally, in-depth discussions and investigations are conducted on key algorithms, such as on-orbit calibration, rapid production of area of interest products, high-definition video geometric stabilization, and multi-angle three-dimensional reconstruction. Finally, the sample dataset is visually displayed and quantitatively evaluated from three aspects: image standard, video staring, and real-world three-dimensional products.
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表 1 雙清一號數(shù)據(jù)技術(shù)指標(biāo)
參數(shù) 指標(biāo)數(shù)值 成像模式 視頻凝視/面陣推幀/面陣推掃 空間分辨率 0.7 m@500 km 地面幅寬 雙CMOS優(yōu)于10 km 視頻幀頻 2~12 Hz 圖像格式 Bayer彩色圖像 量化位數(shù) 8 bit/12 bit 幾何定位精度 優(yōu)于30 m 相對輻射精度 優(yōu)于3% 下載: 導(dǎo)出CSV
1 傳感器校正算法
輸入:分片影像、成像時間、姿軌數(shù)據(jù)、地球自轉(zhuǎn)參數(shù)、高程
dem等輸出:有理函數(shù)模型RFM和虛擬大影像 1 分別構(gòu)建單片原始影像和待校正虛擬影像的嚴(yán)格幾何成像模
型:
$\left[ \begin{gathered} X \\ Y \\ Z \\ \end{gathered} \right] = \dfrac{1}{\lambda } \cdot R_{ {\rm{J2000} } }^{ {\rm{WGS84} } }(t)R_{ {\rm{body} } }^{ {\rm{J2000} } }(t)R_{ {\rm{senor} } }^{ {\rm{body} } }\left[ \begin{gathered} x + {x_0} + \Delta x \\ y + {y_0} + \Delta y \\ f \\ \end{gathered} \right] + \left[ \begin{gathered} {X_{ {\rm{GPS} } } }(t) \\ {Y_{ {\rm{GPS} } } }(t) \\ {Z_{ {\rm{GPS} } } }(t) \\ \end{gathered} \right]$2 建立分片原始影像與待校正虛擬影像的坐標(biāo)映射關(guān)系; ${(s,l)}_{ {\rm{ori} } }\iff {(x,y)}_{{\rm{vir}}},其中{(s,l)}_{ {\rm{ori} } }\Rightarrow (B,L,H)\Rightarrow {(x,y)}_{ {\rm{dst} } }$ 3 影像重采樣(CUDA并行) 3.1 對單片原始影像進(jìn)行格網(wǎng)劃分,每個格網(wǎng)(grid)包含
$(w \times h)$個像素3.2 設(shè)定CUDA線程參數(shù),包括: (a) 每個CUDA格網(wǎng)(grid)中的塊(block)數(shù)目:$({B_x},{B_y})$ ; (b) 每個CUDA塊(block)中的線程(thread)數(shù)目:$({T_x},{Y_y})$; (c) 每個CUDA線程(thread)中處理的像素數(shù)目:$({P_x},{P_y})$ 確保$({B_x} \times {T_x} \times {P_x},{B_y} \times {T_y} \times {P_y}) \ge (w \times h)$ 3.3 每個格網(wǎng)(grid)中的$ ({B_x} \times {T_x},{B_y} \times {T_y}) $個線程(thread)
并行執(zhí)行:每個線程處理$({P_x},{P_y})$個像素 每個像素 (a) 計算虛擬影像像點$ {(x,y)_{{\rm{vir}}}} $所對應(yīng)單片原始影像像
點坐標(biāo)${(s,l)_{{\rm{ori}}}}$;(b) 分別計算像點${(s,l)_{{\rm{ori}}} }$鄰域像素的灰度值; (c) 利用多項式重采樣方法,計算出${(s,l)_{{\rm{ori}}} }$灰度值. 像素循環(huán)結(jié)束 影像格網(wǎng)循環(huán)結(jié)束 下載: 導(dǎo)出CSV
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