現代衛星影像獲得之技術突飛猛進，雖然提供了前所未有的豐富資訊量，但也因外在環境造成了影像判讀的問題，「MODIS衛星影像」因涵蓋範圍廣、每日可接收二次資料、以及免費使用等優點，已獲得相關領域研究者廣泛使用，其研究結果對全球的陸地、海洋、生物圈及大氣等長時間的監測均有助益。
然而，MODIS衛星影像為被動式光學影像，本身常因大氣雲霧干擾，致使影像品質遭受影響而無法使用。因此，為解決此一現象，本研究試圖以同態濾波法、小波分解與融合之方法、以及多尺度視網膜技術，其目的在於濾除MODIS衛星影像之薄霧，使無法判讀之影像轉為可使用之資料。本研究比較分析上述三種方法實驗結果，以決定何種方法較適合MODIS衛星影像薄霧濾除。
另外，也針對濾除薄霧後之MODIS衛星影像進行海洋內波特徵擷取的分析，以驗證本研究方法在濾除MODIS衛星影像薄霧方面的效益。實驗結果發現多尺度視網膜技術（MSR）在濾除薄霧時間較同態濾波法及小波分解與融合法為「慢」；但在邊緣偵測結果，則是以多尺度視網膜技術為較佳。此外，同態濾波法以及小波分解與融合法確能有效濾除薄霧並對海洋內波特徵擷取效果有明顯助益。
最後，本研究利用多尺度線性特徵提取演算法，試圖改善邊緣偵測法所擷取之特徵線精簡後的分岔及斷裂等現象，實驗結果顯示，所擷取的特徵線明顯是海洋內波主要特徵線，雲霧陰影線及波浪線得已排除。

The technology that modern satellite image obtains advances by leaps and bounds, though has offered unprecedented abundant amount of information. However, the external environment has caused the problem of image interpretation. There are many advantages for MODIS satellite image including the global coverage, receiving twice every day, and free cost etc. It has been accepted and applied by relevant earth scientists extensively. These study results benefit long-term global land, ocean, biosphere, and atmosphere monitoring.
MODIS satellite image is a passive-type optic image. Its image quality and availability is influenced usually by atmosphere cloud or haze. In order to solve this problem, this research attempts to use three methods of haze removal for MODIS satellite image including Homo-morphic filter, Wavelet transform and fusion, and Multi-scale Retinex. These haze removal methods are applied to extract useful information form damaged MODIS images. The results are compared and analyzed to determine which method is suitable for the haze removal in the study.
The experimental results show that Multi-scale Retinex is slower than both of the Homo-morphic filter, and Wavelet transform and fusion. However, according to the Canny edge detection method applied to above results, the Multi-scale Retinex is better than the other two methods. In addition, these three methods can really remove haze and it is benefit to the oceanic internal waves feature detection.
Finally, this research performed a Multi-scale linear feature extraction algorithm to extract the visual distinct major linear feature of oceanic internal waves. The shade lines of cloud and haze have been also removed.

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[24]http://rapidfire.sci.gsfc.nasa.gov/realtime/single.php?orbitmap2.
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