本文選題：大氣校正 + 大氣傳輸模型　； 參考：《航天返回與遙感》2017年05期

【摘要】：大氣散射、吸收及臨近效應(yīng)等降低了大氣調(diào)制傳遞函數(shù)而影響遙感圖像清晰度,去除大氣影響對(duì)提高圖像清晰度具有重要意義。文章采用典型遙感衛(wèi)星Landsat-8多光譜數(shù)據(jù)進(jìn)行大氣校正對(duì)圖像清晰度提升的研究,基于6S模型、FLAASH模型和黑暗像元法(DOS)模型進(jìn)行大氣校正,得到各譜段地物反射率圖像。采用常用的基于圖像特征參數(shù)(灰度梯度、邊緣、熵及頻譜)和多光譜圖像色彩保真度的清晰度評(píng)價(jià)方法對(duì)校正前后圖像清晰度進(jìn)行評(píng)價(jià)。結(jié)果表明:采用FLAASH、6S和DOS三種模型,大氣校正后的清晰度特征參數(shù)(以熵為例)較原圖平均提升程度分別為27%、10%、1.3%。而色彩保真度方面,各譜段反射率與實(shí)際反射率差(以草地為例)的平均值分別為0.018、0.028、0.038。因此,基于輻射傳輸模型的方法具有更高的大氣校正精度,其中FLAASH模型對(duì)圖像清晰度的提升最明顯。
[Abstract]:Atmospheric scattering, absorption and proximity effects reduce the atmospheric modulation transfer function and affect the clarity of remote sensing images. Removing the atmospheric effects is of great significance to improve the image clarity. In this paper, the atmospheric correction of typical remote sensing satellite Landsat-8 multispectral data is used to improve the image sharpness. Based on the 6S model FLAASH model and the dark pixel method (DOS) model, the atmospheric correction is carried out, and the reflectivity images of each spectral region are obtained. The definition evaluation methods based on image feature parameters (grayscale gradient, edge, entropy and spectrum) and color fidelity of multi-spectral images were used to evaluate the image clarity before and after correction. The results show that by using the three models of FLAASHZ6S and DOS, the sharpness parameters (entropy as an example) after atmospheric correction are 27 1010 / 1.3, respectively, compared with the original map. In terms of color fidelity, the average value of reflectivity difference between each spectral segment and the actual reflectivity (taking grassland as an example) is 0.018 / 0.028 / 0.038, respectively. Therefore, the method based on radiative transfer model has higher atmospheric correction accuracy, and the FLAASH model can improve the image sharpness most obviously.
【作者單位】： 北京空間機(jī)電研究所;
【分類號(hào)】：TP751
，

本文編號(hào)：1937237