本文選題：數(shù)字高程模型　切入點(diǎn)：水平分辨率　出處：《南京師范大學(xué)》2014年博士論文　論文類型：學(xué)位論文

【摘要】：作為國(guó)家地理信息的基礎(chǔ)數(shù)據(jù),數(shù)字高程模型(Digital Elevation Model, DEM)是國(guó)家空間數(shù)據(jù)基礎(chǔ)設(shè)施(NSDI)的框架數(shù)據(jù),在國(guó)民經(jīng)濟(jì)和國(guó)防建設(shè)中具有重要的應(yīng)用。在當(dāng)今不同比例尺、不同分辨率、不同精度的DEM共存局面下,DEM尺度問題是急需解決的熱點(diǎn)問題,這不僅是DEM和地學(xué)模型在集成上的根本保證,也是DEM數(shù)據(jù)推廣和應(yīng)用的關(guān)鍵所在。因此,DEM分辨率計(jì)算與轉(zhuǎn)換成為DEM生產(chǎn)者與應(yīng)用部門的重要研究命題之一。 本文從原始散點(diǎn)數(shù)據(jù)入手,探索滿足DEM地形表達(dá)要求的分辨率計(jì)算方法,當(dāng)計(jì)算所得的分辨率不能與實(shí)際應(yīng)用相匹配時(shí),經(jīng)常需要尺度轉(zhuǎn)換。針對(duì)這一問題,本文基于分形、小波等數(shù)學(xué)理論,結(jié)合DEM的地形表達(dá)、地形分析,對(duì)DEM的分辨率計(jì)算和尺度轉(zhuǎn)換進(jìn)行了系統(tǒng)的研究,主要研究成果如下： (1)提出了基于分形理論的DEM分辨率確定方法。DEM是對(duì)地表形態(tài)的表達(dá),應(yīng)最大限度的反應(yīng)地形信息量。這就需要從原始數(shù)據(jù)入手,探索DEM分辨率的確定方法。運(yùn)用分形定量表達(dá)地形自相似性及復(fù)雜性的特性,建立了DEM分辨率與分形信息維數(shù)的關(guān)系,通過直線斜率差值尋求能夠最大限度描述地形信息的拐點(diǎn),從而確定DEM水平分辨率。 (2)研究了基于多進(jìn)制小波分解的DEM尺度上推算法。從DEM的實(shí)際應(yīng)用需求出發(fā),建立了DEM尺度上推的基本原則。顧及DEM尺度上推精度因素,構(gòu)建了一種基于隨機(jī)數(shù)的DEM尺度上推算法。利用多進(jìn)制小波的多分辨率分析、多尺度分析特性,提出了一種基于多進(jìn)制小波分解的DEM尺度上推方法,通過DEM的多進(jìn)制小波分解,得到的低頻部分即作為中低分辨率的DEM,并對(duì)該方法及常用的重采樣方法進(jìn)行對(duì)比分析。 (3)提出了一種基于多進(jìn)制小波與插值結(jié)合的DEM尺度下推算法。首先利用多進(jìn)制小波分解,將得到的高頻部分進(jìn)行雙線性插值并與原始DEM數(shù)據(jù)做為低頻的部分,通過多進(jìn)制小波逆變換得到尺度下推后的DEM數(shù)據(jù),并對(duì)實(shí)驗(yàn)結(jié)果進(jìn)行了主客觀評(píng)價(jià)。 (4)提出了一種多進(jìn)制小波與濾波的DEM尺度下推算法。顧及多進(jìn)制小波的方向性,將方向?yàn)V波作用于DEM數(shù)據(jù)上,構(gòu)建DEM高頻部分,并與原始DEM數(shù)據(jù)通過多進(jìn)制小波重構(gòu)得到尺度下推的DEM數(shù)據(jù),并與上一算法進(jìn)行比較分析。 (5)在對(duì)基于學(xué)習(xí)的圖像超分辨率重建算法分析的基礎(chǔ)上,提出了一種基于DEM非局部相似性約束的鄰域重構(gòu)DEM尺度下推算法。通過獲取部分高分辨的DEM數(shù)據(jù),基于子區(qū)域的相似性和領(lǐng)域相容性,在低分辨率DEM數(shù)據(jù)中,尋找待尺度下推數(shù)據(jù)的非局部相似子區(qū)域,根據(jù)相似程度,將高分辨率數(shù)據(jù)映射到對(duì)應(yīng)的區(qū)域,從而完成DEM的尺度下推,并與插值算法及多進(jìn)制小波重構(gòu)的DEM尺度下推算法進(jìn)行對(duì)比分析。
[Abstract]:As the basic data of national geographic information, Digital elevation Model (demm) is the frame data of National Spatial data Infrastructure (NSDI), which has important applications in national economy and national defense construction. Dem scale problem in the coexistence of DEM with different precision is a hot issue that needs to be solved urgently, which is not only the fundamental guarantee of integration of DEM and geoscience model. It is also the key of DEM data popularization and application, so Dem resolution calculation and conversion become one of the important research propositions of DEM producers and application departments. Starting from the original scattered point data, this paper explores a resolution calculation method that meets the requirements of DEM topographic representation. When the calculated resolution does not match with the actual application, scale conversion is often required. In view of this problem, this paper is based on fractal. Wavelet and other mathematical theories, combined with the terrain representation and terrain analysis of DEM, systematically study the resolution calculation and scale conversion of DEM. The main research results are as follows:. 1) this paper puts forward the DEM resolution determination method based on fractal theory. Dem is the representation of surface morphology, which should reflect the maximum amount of topographic information, which needs to start with the original data. The determination method of DEM resolution is explored. The relationship between DEM resolution and fractal information dimension is established by using fractal quantification to express the characteristics of terrain self-similarity and complexity. The inflection point which can describe the topographic information to the maximum extent is found by the linear slope difference, and the horizontal resolution of DEM is determined. In this paper, the method of DEM scaling estimation based on multiary wavelet decomposition is studied. Based on the practical application requirements of DEM, the basic principle of DEM scale upscaling is established. The factors of DEM scale push-up accuracy are taken into account. In this paper, a DEM scale upscaling method based on random number is constructed. By using the multi-resolution analysis and multi-scale analysis characteristic of the multi-ary wavelet, a DEM scale up-scaling method based on the multi-ary wavelet decomposition is proposed, which is based on the multi-ary wavelet decomposition of DEM. The obtained low-frequency part is regarded as the low resolution DEM, and the method and the resampling method are compared and analyzed. In this paper, we propose a DEM scaling algorithm based on the combination of multiary wavelet and interpolation. Firstly, the bilinear interpolation of the obtained high frequency part and the original DEM data are used as the low-frequency part by using the multi-ary wavelet decomposition. The DEM data of the scale are obtained by inverse wavelet transform, and the experimental results are evaluated objectively and subjectively. In this paper, a DEM scale estimation method based on multiary wavelet and filter is proposed. Considering the directivity of multiary wavelet, the directional filtering is applied to the DEM data, and the high frequency part of DEM is constructed. The scale derived DEM data are reconstructed from the original DEM data by multi-ary wavelet, and compared with the previous algorithm. 5) based on the analysis of Learn-based super-resolution image reconstruction algorithm, a neighborhood reconstruction DEM scale extrapolation method based on DEM nonlocal similarity constraints is proposed. Some high-resolution DEM data are obtained. Based on the similarity of subregions and domain compatibility, the non-local similar sub-regions of the data to be pushed down to scale are found in low-resolution DEM data, and the high-resolution data are mapped to the corresponding regions according to the similarity degree. Thus, the scale deduction of DEM is completed, and compared with the interpolation algorithm and the DEM scale extrapolation method of multi-ary wavelet reconstruction.
【學(xué)位授予單位】：南京師范大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：P208

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