太空衛星視訊是人類觀測地表的重要資訊來源。隨著技術的演進，我們從衛星取得的資料不再只是過往的單張低解析度影像，而是高解析度的視訊。本論文旨在利用這種高解析衛星視訊做多物件追蹤。
我們的方法是先做物件偵測後再做物件追蹤，物件偵測部分是使用連續眾數建構背景取代演算法，藉此取得前景後，再分別把移動物件分成三類分別處理，分別是：大型移動物件、小型水上移動物件、小型陸上移動物件。其中，針對小型水上移動物件，我們建構一個陸地遮罩來區隔水陸。針對小型陸上移動物件，我們特別建構一個建築物遮罩來避免建築物所產生的錯誤。在這之後，再根據所有前景作一些形態學濾波過濾雜訊。
物件追蹤的部分，針對每個物體分別計算其速度來預測位置。而針對物件追蹤常出現的物件黏合問題，當偵測到有黏合發生時，偵測該區域的區域極值做匹配。

Spaceborne remote sensing videos are important resources for us to observe earth. With the advance of science and technology, the sources from satellites are not just low resolution images but high resolution videos. The objective of this Thesis is to do multi-object tracking with high resolution satellite videos.
The proposed algorithm is separated into two parts: object detection and object tracking. In object detection, continuous mode is used to build the background model. After getting the foreground with the background model, foreground after noise elimination is classified into three possible categories: big objects, small water objects, and small ground objects. For small water objects, a ground mask is built to separate water and ground. For small ground objects, a building mask is constructed to avoid the error that causes by buildings. Then the foreground is further processed through a mathematical morphology filter.
In object tracking, the speeds of objects are calculated to predict their locations. Occlusion is a problem of object tracking. When the occluded objects are detected, local extremums are computed to separate objects.

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