應用影像分割技術與碎形理論於福衛二號Quick-Look影像之雲覆蓋萃取

Using Segmentation Techniques and Fractal Theory to Extract Cloud Coverage for Formosat-2 QUICK-LOOK Images

張立雨(L. Y. Chang) ； 陳繼藩(C. F. Chen) ； 陳哲俊(A. J. Chen) ； 林欣穎(H. Y. Lin)

《航測及遙測學刊》 12卷3期 (2007/09) Pp. 273-281

https://doi.org/10.6574/JPRS.2007.12(3).6

摘要

對於應用光學衛星影像進行地面各項土地資源調查而言，影響影像可用度之最大因素即爲影像之含雲量。因此對於所接收到之影像若能快速的提供相關雲覆蓋量之評估，不但對於影像使用者在選擇影像上有更良好之參考，也能在影像接收上提供適當資訊以作爲未來接收規劃之依據。目前，福衛二號衛星影像在雲量評估上主要是利用系統所產生之QUICK-LOOK影像進行人工判釋，而QUICK-LOOK影像爲衛星影像接收系統產生作爲影像檢索用途之影像。而應用QUICK-LOOK影像進行雲覆蓋判釋時，主要是先將原始QUICK-LOOK影像分割爲八等分，並且在每等分中以人工方式給定五種等級之雲覆蓋指標來標示雲含量之多寡。此項指標除必須花費較多時間進行人工判釋外，並且其結果常會受到操作者之主觀認定而受影響。同時，僅使用五種等級所產生之雲覆蓋資訊對於實際應用上亦略顯不足。因此本研究提出利用影像分割並配合碎形理論之分析方法對QUICK-LOOK影像進行定量且自動化之雲覆蓋評估。方法上主要先利用區塊成長進行影像分割後，再利用非監督性分類法K-MEAN將分割後之區塊進行非監督性分類來產生訓練雲區區塊。最後利用所產生之訓練雲區區塊計算雲區之碎形特性，並以此碎形特性進行所有雲區區塊之萃取。研究成果顯示，將所產生之結果轉換爲相當人工判釋所得之雲量指標後再與人工判釋之結果比較，其結果顯示兩者具有一致性。

關鍵字

QUICK-LOOK影像 ； 雲區覆蓋量評估 ； 碎形理論

並列摘要

The percentage of cloud coverage is generally considered the most important factor to affect the availability of optical satellite images for land resource applications. Consequently, an effective cloud assessment process can not only offer general users a guideline for image browsing, but also provide valuable information for orbit planning of ground receiving station. At present, the cloud coverage of Formosat-2 data is visually examined and manually estimated by the operators on the QUICK-LOOK images. The QUICK-LOOK images basically are the reduced images created by satellite data receiving system for browsing purpose. As to the current estimation of cloud coverage, every QUICK-LOOK image is divided into 8 portions and the cloud coverage for each portion is indicated with a cloud index with 5 grades. Apparently, the visual and manual cloud assessment method is labor-intensive, time-consuming, and dependent on the operator’s experience. Furthermore, the existing 5-grade cloud index is inadequate to describe the accurate percentage of cloud coverage. Thus, there is an urgent need for developing an automatic approach for cloud assessment. In this study, a two-stage scheme based on image segmentation and fractal theory is used to automatically extract cloud pixels from QUICK-LOOK images. The experimental results indicate that the cloud areas extracted by proposed scheme are very similar to the manual interpretation. In addition, when the automatically extracted cloud coverage is transferred to the existing cloud index, a good agreement between our automatic approach and current manual estimation is achieved.

並列關鍵字

QUICK-LOOK image ； Cloud assessment ； Fractal theory