最後對本論文的方法做一個總結，本論文所提出的一個基於粒子群演算法與 Canny 邊緣偵測來改善離散小波轉換和奇異值分解的數位浮水印技術。主要是利 用 DWT 和 SVD 轉換，藉由 Canny 濾波器，將浮水印嵌入於頻率域的邊緣特徵 裡，在以粒子群演算法，找出浮水印在不可視性與強韌性之間的合適權重。實驗 結果證實，本論文的方法，所計算出來的 PSNR，有明顯高於其他方法。而且，
再承受幾何攻擊、雜訊攻擊，去雜訊攻擊，壓縮攻擊，其他影像處理攻擊這五項 攻擊時，也具備極佳的抵抗效果；而且，在大多數的攻擊中，本論文所計算出來 的 Q 值，都位居第一。至於，在未來的工作上，將會針對以下的幾大項，進行 更深入的研究探討。
特徵擷取：
1. 運用更多的邊緣偵測濾波器，進行嵌入測試。
2. 分析影像的角點、紋理、與內容。
3. 藉由DCT進行特徵擷取，並找出最佳嵌入位置。
頻域轉換技術：
1. 利用 DFT 或 DCT，加強浮水印抗攻擊的強韌度。
2. 比較 DFT、DCT 與 DWT 在不同頻域段的強韌度。
粒子群最佳化設計：
1. 給予浮水印不可視性與強韌性不同的比重，來改善適應函數上的設計。
2. 運用更多的影像品質評估函式，來進行適應函數的設計。
3. 加入更多具代表性的攻擊，來改進適應函數的設計。
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