發(fā)布時(shí)間：2018-06-19 19:51

  本文選題：資源三號(hào)衛(wèi)星 + 衛(wèi)星影像��； 參考：《武漢大學(xué)學(xué)報(bào)(信息科學(xué)版)》2016年09期

【摘要】：云噪聲是光學(xué)衛(wèi)星影像的常見(jiàn)問(wèn)題,為了衡量云噪聲對(duì)影像融合帶來(lái)的影響,本文以高通濾波融合算法為例進(jìn)行分析,指出云與地物的均值相差越大,云對(duì)影像融合的影響越大,并提出了一種針對(duì)含云影像的融合方法,即聯(lián)合云檢測(cè)與高通濾波的含云影像融合方法。該方法首先利用NIR/R-OTSU云檢測(cè)算法實(shí)時(shí)進(jìn)行云檢測(cè),判別出影像中的云覆蓋區(qū)域;其次采用局部?jī)?yōu)化策略利用高通濾波融合方法分塊對(duì)非云區(qū)域進(jìn)行處理,得到融合影像。利用資源三號(hào)多光譜和正視全色影像進(jìn)行融合實(shí)驗(yàn),結(jié)果表明,本文算法比高通濾波融合方法、亮度色度飽和度(intensity hue saturation,IHS)變換融合方法、Pansharp融合方法更適用于含云影像的融合處理。
[Abstract]:Cloud noise is a common problem of optical satellite images. In order to measure the influence of cloud noise on image fusion, this paper takes high pass filtering fusion algorithm as an example to show that the greater the difference between the mean value of the cloud and the terrain, the greater the influence of cloud to image fusion, and a fusion method for cloud images, namely, joint cloud detection and detection, is proposed. The method of cloud image fusion with high pass filtering. This method first uses NIR/R-OTSU cloud detection algorithm to detect cloud in real time to distinguish the cloud coverage area in the image. Secondly, the local optimization strategy is used to process the non cloud region by high pass filtering fusion method, and the fusion image is obtained. The multi spectrum and the full view of resource three are used. The color image fusion experiment shows that the algorithm is better than the high pass filtering fusion method, the intensity hue saturation, IHS transform fusion method, and the Pansharp fusion method is more suitable for the fusion processing of the cloud image.
【作者單位】： 武漢大學(xué)遙感信息工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(41322010,41301519) 國(guó)家863計(jì)劃(2013AA12A401)~~
【分類號(hào)】：P237;TP751
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本文編號(hào)：2041063