本文選題：線性光譜混合分解 + 混合像元　； 參考：《測(cè)繪學(xué)報(bào)》2017年11期

【摘要】：高時(shí)間分辨率遙感影像在地表景觀破碎區(qū)域易形成混合像元,難以發(fā)揮其高時(shí)間維度優(yōu)勢(shì)。現(xiàn)有方式多是基于線性光譜混合模型,借助鄰域像元所構(gòu)成的像元集合組成線性方程組,求出組分光譜值的最小二乘解,提高其空間分辨率。然而,現(xiàn)有方法依賴窗口形式來(lái)構(gòu)建鄰域像元集合,在某些區(qū)域易造成方程組無(wú)解的欠定問(wèn)題。本文在分析其問(wèn)題原因的基礎(chǔ)上,引入阿基米德螺線代替?zhèn)鹘y(tǒng)的矩形窗口,對(duì)鄰域各像元依次遍歷,構(gòu)建空間鄰近、組分相近的鄰域像元集合來(lái)解決該問(wèn)題。在GlobeLand 30數(shù)據(jù)上的試驗(yàn)表明,螺線型構(gòu)建方法對(duì)5種混合尺度上多種類型地物均具有穩(wěn)定的精度,與傳統(tǒng)窗口構(gòu)建方法相比,可從構(gòu)建鄰域像元集合方面將總體理論精度提高2%,分解結(jié)果精度提高近1個(gè)數(shù)量級(jí)。
[Abstract]:High time resolution remote sensing images are easy to form mixed pixels in the broken area of surface landscape, so it is difficult to give full play to the advantage of high time dimension. Most of the existing methods are based on the linear spectral mixing model. By means of the pixel set formed by the neighborhood pixel, the least square solution of the spectral value of the component is obtained and its spatial resolution is improved. However, the existing methods rely on the window form to construct the set of neighborhood pixels, which can lead to the unsolvable problem of equations in some regions. In this paper, based on the analysis of the causes of the problem, Archimedes spiral is introduced to replace the traditional rectangular window, the neighborhood pixels are traversed in turn, and the adjacent pixel sets with adjacent space and similar components are constructed to solve the problem. Experiments on GlobeLand 30 data show that the spiral construction method has a stable accuracy for many types of ground objects on five mixed scales, compared with the traditional window construction method. From the aspect of constructing neighborhood pixel set, the total theoretical accuracy can be improved by 2 and the resolution result accuracy can be improved by nearly one order of magnitude.
【作者單位】： 吉林大學(xué)地球探測(cè)科學(xué)與技術(shù)學(xué)院;國(guó)家基礎(chǔ)地理信息中心;中國(guó)礦業(yè)大學(xué)(北京)地球科學(xué)與測(cè)繪工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目(41231172)~~
【分類號(hào)】：P237
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本文編號(hào)：1816643