Fisher準則函數暨最鄰近特徵空間演算法 應用於多源遙測資料融合之崩塌地影像分類

Multisource Data Fusion and Fisher Criterion Based Nearest Feature Space Approach to Landslide Classification

王怡鈞(Yi Chun (Benny) Wang)

指導教授 ： 張陽郎

國立臺北科技大學/電資學院/電機工程系博士班/博士(2014年)

https://doi.org/10.6841/NTUT.2014.00450

摘要

近六年來，因強烈颱風及地震所造成崩塌地及土石流的地理災害現象，已佔臺灣本島重大天然災害七成以上的比率。因此，崩塌地的形成、危險地區的判斷、發生的機率與降低災害的防治，已引發眾多產官學的極大重視與研究。藉此，我們提出一新方法:波段生成法( Band Generation Process, BGP）Fish準則函數暨最鄰近特徵空間演算法(Fisher Criterion based nearest feature space, FCNFS)，針對多源多頻遙測資料融合的崩塌地影像,進行經濟有效的監督式分類。本論文應用波段生成法BGP與FCNFS分類器的組合，達成多源多頻譜遙測資料的融合。針對土地覆蓋類別-崩塌地的多源遙測之原始資料，使用BGP進行萃取並產生一組新的波段，進而增加該測試類別的波段數，以俾提高最鄰近特徵空間演算法 (NFS) 的分類效益。有別於傳統NFS的演算過程，我們在樣本訓練程序中，應用Fisher準則函數同異類別的區隔特性，將之視為NFS演算法的前段處理，進而強化其分類的正確率。

由實驗的結果證明，本論文所提出BGP/FCNFS的方法，適用於多源多頻譜遙測資料融合的崩塌地影像，包含其他七種土地覆蓋的分類，諸如，道路、旱地、池塘、森林、河川、建築物及農地。最後，依據其與傳統多頻譜遙測影像資料分類方法的效能比較結果，印證其為可提供較佳正確率的方法。

關鍵字

頻道產生程序 ； 分類 ； Fisher準則函數 ； 崩塌地 ； 多源資料融合 ； 最鄰近特徵向量空間

並列摘要

In this dissertation, a novel technique known as the Fisher criterion based nearest feature space (FCNFS) approach is proposed for supervised classification of multisource images for the purpose of landslide hazard assessment. The method is developed for land cover classification based upon the fusion of remotely sensed images of the same scene collected from multiple sources. This dissertation presents a framework for data fusion of multisource remotely sensed images, consisting of two approaches: the band generation process (BGP) and the FCNFS classifier. The multiple adaptive BGP is introduced to create an additional set of bands that are specifically accommodated to the landslide class and are extracted from the original multisource images. In comparison to the original nearest feature space (NFS) method, the proposed FCNFS classifier uses the Fisher criterion of between-class and within-class discrimination to enhance the classifier. In the training phase, the labeled samples are discriminated by the Fisher criterion, which can be treated as a pre-processing step of the NFS method. After completion of the training, the classification results can be obtained from the NFS algorithm. Experimental results show that the proposed BGP/FCNFS framework is suitable for land cover classification in Earth remote sensing and improves the classification accuracy compared to conventional classifiers.

並列關鍵字

band generation process ； classification ； Fisher criterion ； landslide ； multisource data fusion ； nearest feature space

參考文獻

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