本文選題：多光譜相機 + 擬合算法　； 參考：《遼寧工程技術大學》2013年碩士論文

【摘要】：多光譜相機可獲取多個波段的影像,通過后續(xù)的配準、融合等處理能夠生成多種專題影像產品,極大地豐富了影像信息同時也提高了影像數(shù)據(jù)的應用潛力。多光譜相機已成為當前遙感衛(wèi)星搭載的重要載荷之一。影響CCD相機波段配準的因素有很多,比如溫度變化和結構穩(wěn)定性等。波段間配準是多光譜影像處理的重要環(huán)節(jié),配準精度直接影響影像數(shù)據(jù)后續(xù)處理和應用價值。由于高程起伏、傳感器內部畸變等因素的影響,衛(wèi)星多光譜相機獲取的影像數(shù)據(jù)波段間通�？赡艽嬖谳^大的非線性幾何變形。因此通過簡單的面平移和旋轉,去實現(xiàn)多光譜影像的波段間配準是無法滿足產品質量的精度要求。對于高空間分辨率衛(wèi)星來說,波段間配準的精度對定位精度、地物分類準確性與可應用性的影響尤為顯著。本文在結合各傳統(tǒng)的遙感圖像配準的基礎上,針對我國環(huán)境衛(wèi)星的特點,對環(huán)境衛(wèi)星多光譜相機四個CCD波段的裝配、運輸及發(fā)射過程中產生的誤差進行評價,最終達到各波段間配準誤差的準確表達的目的。本文在配準算法和亞像元定位技術的基礎上,提出了幾種專門針對環(huán)境衛(wèi)星特性的波段配準精度評價的算法。其中包括灰度質心算法、高斯曲線擬合算法、霍夫變換交點算法、高斯曲面擬合算法以及基于特征地物評價算法。這些算法分別從影像的灰度結構、邊緣曲線的性質、局部曲面的性質以及影像特征區(qū)域灰度的分布特性等方面對影像的配準誤差進行了詳細的評述�；谶@些算法,本文計算了環(huán)境衛(wèi)星多光譜相機CCD波段間配準誤差分別在沿軌和跨軌方向上的數(shù)值大小。計算結果顯示環(huán)境CCD二級產品各波段之間的配準誤差基本小于0.5個像素,部分數(shù)據(jù)可以達到0.1個像素之內。幾種算法都可以獲得比較穩(wěn)定的評價結果,從而達到了從多方面對波段間配準誤差的評價,相互驗證了計算結果的證確性。
[Abstract]:Multi-spectral camera can obtain multiple bands of images. Through subsequent registration, fusion and other processing can generate a variety of thematic image products, greatly enriched the image information, but also improved the application potential of image data. Multispectral camera has become one of the important payloads of remote sensing satellite. There are many factors affecting CCD camera band registration, such as temperature variation and structural stability. Inter-band registration is an important part of multi-spectral image processing. Registration accuracy directly affects the image data processing and application value. Due to the influence of height fluctuation and internal distortion of sensor, there may be large nonlinear geometric deformation between the bands of image data obtained by satellite multispectral camera. Therefore, it can not meet the precision requirement of product quality by simple surface translation and rotation to achieve the registration of multi-spectral images between bands. For high spatial resolution satellites, the accuracy of registration between bands has a significant effect on positioning accuracy, classification accuracy and applicability of ground objects. Based on the traditional remote sensing image registration and the characteristics of Chinese environmental satellites, this paper evaluates the errors in the process of assembling, transporting and launching four CCD bands of environmental satellite multispectral cameras. Finally, the accurate expression of registration error between different bands is achieved. On the basis of registration algorithm and sub-pixel location technology, this paper presents several algorithms for evaluating the band registration accuracy of environmental satellites. It includes gray centroid algorithm, Gao Si curve fitting algorithm, Hough transform intersection algorithm, Gao Si surface fitting algorithm and feature based feature evaluation algorithm. In this paper, the image registration errors are reviewed in detail from the aspects of the gray structure of the image, the properties of the edge curve, the properties of the local surface and the distribution of the gray level in the feature region of the image. Based on these algorithms, the magnitude of the registration error between CCD bands of environmental satellite multispectral camera is calculated in the direction of orbit and trans-orbit, respectively. The results show that the registration error is less than 0.5 pixels and part of the data can be within 0.1 pixels. Several algorithms can obtain relatively stable evaluation results, which can evaluate the registration error between bands from many aspects, and verify the validity of the calculation results.
【學位授予單位】：遼寧工程技術大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：P237

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