【摘要】：尺度轉(zhuǎn)換是遙感信息科學(xué)領(lǐng)域的研究熱點(diǎn),其傳統(tǒng)研究方法大多局限于統(tǒng)計模型,對數(shù)據(jù)的空間結(jié)構(gòu)信息考慮較少,很難滿足遙感數(shù)據(jù)的多尺度表達(dá)要求�；诖�,針對遙感數(shù)據(jù)的尺度不一致問題,本文提出了一種利用高斯金字塔的圖像模糊特性進(jìn)行遙感數(shù)據(jù)尺度上推的方法,在對金字塔每一層的數(shù)據(jù)高斯模糊的基礎(chǔ)上,通過多次連續(xù)的降采樣,得到一系列不同尺度的數(shù)據(jù),從而滿足實際應(yīng)用的空間分辨率要求。為了驗證本文所提方法的有效性,本文選擇Landsat7 ETM影像和ASTER GDEM為研究數(shù)據(jù)進(jìn)行尺度上推,并與傳統(tǒng)的最鄰近、雙線性以及立方卷積等方法進(jìn)行了實驗對比,采用均值、方差、均方根誤差、平均絕對誤差等評價指標(biāo),以及相同分辨率的ASTER GDEM和SRTM DEM的等高線套合結(jié)果來衡量高斯金字塔方法的性能。實驗結(jié)果表明,本文使用的高斯金字塔尺度上推方法能夠有效地實現(xiàn)連續(xù)遙感數(shù)據(jù)的尺度轉(zhuǎn)換,在保持遙感數(shù)據(jù)局部細(xì)節(jié)特征的基礎(chǔ)上,較好地保持了原始遙感數(shù)據(jù)的信息量以及空間結(jié)構(gòu)特征。
[Abstract]:Scale conversion is a hot topic in the field of remote sensing information science. Its traditional research methods are mostly confined to statistical models, and the spatial structure information of data is less considered, so it is difficult to meet the requirements of multi-scale representation of remote sensing data. Based on this, aiming at the problem of scale inconsistency of remote sensing data, this paper proposes a method to push up the scale of remote sensing data by using the fuzzy characteristics of Gao Si's image. A series of data of different scales are obtained by several successive demultiplexing, which meet the spatial resolution requirements of practical applications. In order to verify the validity of the proposed method, Landsat7 ETM image and ASTER GDEM are selected as the data to be used for scaling up, and the experimental results are compared with the traditional methods such as nearest neighbor, bilinear and cubic convolution. The mean value, variance and variance are used. The performance of Gao Si pyramid method is evaluated by the RMS error, the mean absolute error and the contour fitting results of ASTER GDEM and SRTM DEM with the same resolution. The experimental results show that Gao Si's pyramid up-scaling method can effectively realize the scale conversion of the continuous remote sensing data, and on the basis of preserving the local detail features of the remote sensing data, The information content and spatial structure of the original remote sensing data are well maintained.
【作者單位】： 中國科學(xué)院遙感與數(shù)字地球研究所;中國科學(xué)院大學(xué);中國地質(zhì)大學(xué)(武漢)計算機(jī)學(xué)院;中國科學(xué)院地理科學(xué)與資源研究所;
【基金】：中國科學(xué)院遙感與數(shù)字地球研究所所長基金項目“基于動態(tài)追蹤樹的區(qū)域計算型GIS空間分析并行化研究(Y6XS6300CX)”
【分類號】：P237

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1 韓鵬;龔健雅;李志林;程亮;;遙感影像空間尺度上推方法的評價[J];遙感學(xué)報;2008年06期

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本文編號：2375968