【摘要】：地質填圖是指對特定區(qū)域的地質年代、地層、構造、礦產(chǎn)資源進行定義、描述、勘查的過程,其比例尺的選取可以根據(jù)實際情況選定,最常用的是1:500-1:50000。 傳統(tǒng)地質工作對某些區(qū)域(如我國喜馬拉雅山脈)進行實地勘查時,由于受這些地區(qū)地理環(huán)境險峻、氣候惡劣等因素影響,會存在勘查盲區(qū)。傳統(tǒng)地質填圖方式中,地質工作人員通常選取特殊地質點進行填圖,如采用1:200000比例尺進行填圖時,每兩平方公里的范圍內(nèi)選取一個地質點進行觀測,這就存在盲區(qū),無法保證填圖的準確性。用人工方式填充一幅1:200000地質圖時,需一個地質大隊(200-300人)工作兩年時間,耗費巨大。 數(shù)字地質填圖方式,借助遙感數(shù)字圖像對整個區(qū)域進行全面詳細、無盲區(qū)地觀察,有利于地質工作人員從時間和空間上對整個地質填圖區(qū)域有一個宏觀的認識和把握,使得地質填圖成果更加貼近客觀實際。 近年來,隨著遙感數(shù)字圖像處理技術在地質填圖中不斷發(fā)展進步,地質工作者越來越意識到其重要性和不可替代性。目前,遙感數(shù)字圖像經(jīng)過相關處理方法變換后作為傳統(tǒng)方式地質填圖時的參考。采用遙感數(shù)字圖像處理技術進行地質填圖過程中存在許多問題。例如,在進行遙感數(shù)字圖像預處理時,存在像素點亮度值丟失、彩色合成圖像顏色偏藍、對比度不適中、不利于目視判讀等問題,導致圖像失真。由于不同衛(wèi)星的不同圖像采集設備對圖像中有效像素的影響是一致的。例如,對不同波段的圖像,如果偏強,則所有有效像素全部偏強；如果偏弱,則所有有效像素全部偏弱。商業(yè)處理軟件處理遙感數(shù)字圖像后,新生成的圖像異常亮點過多,對比度過強,這些都影響到遙感數(shù)字圖像原始信息的提取,最終影響到地質填圖的實施和可信度。 目前,所采用的各種遙感數(shù)字圖像對比度增強和彩色合成增強方法,都存在不能有效解決像素點亮度值經(jīng)過增強后損失的問題。如何將遙感數(shù)字圖像中含有的原始數(shù)據(jù)信息完整無損的提取出來,正是我們要考慮和解決的問題。這直接關系到主成分分析、小波變換等后續(xù)工作的順利展開,從而為地質填圖打下堅實的基礎。 本研究以無損平移雙向對比度拉伸算法為理論基礎,嘗試提出一種盡量減少像素點亮度值丟失的改進算法,為遙感數(shù)字圖像處理后續(xù)工作的展開提供堅實基礎。采用遙感數(shù)字圖像處理技術直接進行地質填圖是世界性難題,我們選取浙江省東部沿海區(qū)域中生代酸性侵入巖為研究對象,首次嘗試利用遙感數(shù)字圖像處理技術進行直接地質填圖。
[Abstract]:Geological mapping refers to the process of defining, describing and exploring the geological age, strata, structure and mineral resources of a particular area. The selection of its scale can be selected according to the actual situation, and the most commonly used is 1: 500-1: 50000. During the field exploration of some areas (such as Himalayan Mountains in China) in the traditional geological work, there will be blind exploration areas due to the influence of such factors as the harsh geographical environment and the bad climate in these areas. In the traditional geological mapping method, geological workers usually select special geological sites for mapping. For example, when mapping on a scale of 1: 200000, one geological spot is selected for observation every two square kilometers, and there are blind areas. There is no guarantee of the accuracy of the mapping. Filling a 1: 200000 geological map manually requires two years of work by a geological unit (200-300 people), which is costly. Digital geological mapping, with remote sensing digital images as a means of comprehensive and detailed observation of the whole region without blind area, is conducive to the geological staff to have a macroscopic understanding and grasp of the whole geological mapping area in time and space. The geological mapping results are closer to the objective reality. In recent years, with the development of remote sensing digital image processing technology in geological mapping, geologists are increasingly aware of its importance and irreplaceable. At present, remote sensing digital image is transformed by correlation processing method as the reference of traditional geological mapping. There are many problems in geological mapping using remote sensing digital image processing technology. For example, in the process of remote sensing digital image preprocessing, there are some problems, such as loss of pixel brightness, blue color of color composite image and unsuitable contrast, which is not conducive to visual interpretation, which leads to image distortion. The effects of different image acquisition devices on the effective pixels in the images are consistent. For example, for images of different bands, all effective pixels are strong if they are strong, and all effective pixels are weak if they are weak. After processing remote sensing digital image by commercial processing software, the newly generated image has too many bright spots and strong contrast, which affects the extraction of original information of remote sensing digital image, and finally affects the implementation and credibility of geological mapping. At present, all kinds of remote sensing digital image contrast enhancement and color combination enhancement methods can not effectively solve the loss of pixel brightness value after enhancement. How to extract the original data information from remote sensing digital image is the problem that we should consider and solve. This is directly related to the smooth development of principal component analysis (PCA) and wavelet transform (WT), thus laying a solid foundation for geological mapping. Based on the theory of lossless translation bidirectional contrast stretching algorithm, an improved algorithm is proposed to minimize the loss of pixel brightness value, which provides a solid foundation for the following work of remote sensing digital image processing. It is a worldwide problem to use remote sensing digital image processing technology to directly map geology. We choose Mesozoic acid intrusive rocks in the eastern coastal area of Zhejiang Province as the research object. It is the first time to use remote sensing digital image processing technology for direct geological mapping.
【學位授予單位】：東北師范大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：P623.6;TP751

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