Complementary Digital Watermarking Technique Based on Wavelet Transformation

摘 要 影像數位浮水印是利用人眼無法察覺影像細微變化的弱點，將特殊的資訊直接嵌入原數位影像中；縱使影像資料經過加解密、壓縮、非惡意的或其它攻擊性的影像處理，所嵌入的資訊依然可偵測出來 在本論文中，提出一種利用小波轉換之互補式浮水印技術做為數位影像資料的保護，在高頻與低頻部份，分別以兩種不同方式，隱藏兩個浮水印，使其在遭受攻擊時，至少有一個浮水印能存活。同時在偵測浮水印過程中不需要原始影像來輔助，因而可節省記憶體儲存空間，且在模擬測試中也證明，可減少原始影像因加入浮水印所造成之失真。 我們針對photoshop 常做之一般影像處理，來驗證加入浮水印之影像經過JPEG壓縮、模糊化、銳利化、雜訊化、圖形裁剪處理後其浮水印偵測結果，結果顯示我們的方法在遭受一般影像攻擊時，大部分都至少有一個浮水印能存活。Abstract Digital image watermark is a technique which takes advantage of the inability of human's eyes to differentiate the subtle change of images. It is a special information embedded and hidden in the original image. Even if the image data is encrypted and decrypted, compressed, unintentional or any other kind of attack, the embedded digital image watermark can still be detected. In this thesis,we propose a complementary watermark technique which uses the skill of wavelet transformation to protect image data. Two complementary watermarks are hidden in the high and low frequencies respectively in the transformed frequency domain. Using this technique , there will be at least one watermark can survive under attack .Besides, in the process of retriever the watermark, the original image isn't needed. Thus,save a lot of memory. The simulation results show that distortion of the original image caused by the insertion of watermark can be minimized. we also examine the outcome of watermark detection under JPEG compression, blurring, sharpening, noise and cutting based on the average image processing skills of Photoshop. The results show that our method can survive from most of the attack.目 錄 第一章 緒論 1 1.1 簡介 1 1.2 動機與目的 4 1.3 論文架構 5 第二章 浮水印背景及小波函數 6 2.1 背景 6 2.1.1 數位浮水印 6 2.1.2 數位浮水印技術要求 7 2.2 小波函數及相關技術 8 2.2.1 小波函數 8 2.2.2 小波函數相關技術 8 2.2.2.1 Haar 8 2.2.2.2 JND 12 2.2.2.3 Quadtree 13 2.2.2.4 Cocktail Watermarking 14 第三章 互補式影像浮水印技術 18 3.1 概述 18 3.1.1 低頻數位浮水印 19 3.1.1.1 低頻數位浮水印加入演算法 19 3.1.1.2 低頻數位浮水印偵測演算法 22 3.1.2 高頻數位浮水印 22 3.1.2.1 高頻數位浮水印加入演算法 22 3.1.2.2 高頻數位浮水印偵測演算法 24 3.1.3 高頻加低頻數位浮水印 25 3.2 系統架構 26 第四章實驗步驟與結果分析實驗結果 28 4.1 軟體測試步驟 29 4.1.1 浮水印加入軟體測試 29 4.1.2 浮水印偵測軟體測試 31 4.2 實驗結果 34 4.2.1 失真壓縮 34 4.2.2 低通濾波模糊化 37 4.2.3 圖形裁剪 38 4.2.4 銳利化 43 4.2.5 雜訊化 44 4.2.6 反交錯式 48 4.2.7 紋理化、擴散光暈 49 4.2.8 雲彩化、鋸齒化 50 4.2.9 風動效果、多面體效果 51 4.2.10 馬賽克效果、去除斑點 52 第五章 結論與未來展望 55 5.1 結論 55 5.2 未來展望 55 參考文獻 5

利用空間統計及權重法進行土石流潛勢溪流

台灣地區因地理環境的因素易受颱風豪雨的侵襲，颱風豪雨除在平原區帶來淹水的災害外在山區也有可能造成嚴重的土石流災害，有鑑於氣候環境的變遷導致降雨型態的改變，評估雨量測站能否滿足土石流防災業務的需求，已是重要之課題。 本研究蒐集大台北地區1998年至2013年颱風及豪雨事件雨量資料，利用克利金推估法計算試驗半變異元，並進行不同模式的理論半變異元套配，透過交叉驗證並引入克利金均方誤差(KAE)及克利金平方誤差(KRMSE)檢定模型適配程度，評估成果顯示雨量站觀測範圍為半徑5公里；透過雨量站觀測範圍評估成果將大台北地區進行網格劃設進行雨量站密度檢討，經評估格網內有土石流潛勢溪流而卻欠缺雨量站網格共計38個；為瞭解各欠缺雨量站格網設站的順序，本研究透過循序演算法及現有雨量站空間特性、等加權因子進行檢討，以評估設站優先順序；最後為瞭解新增雨量站的效益，本研究利用克利金變異數推估與空間分析，經評估各區潛勢溪流與鄰近雨量站距離均可縮減至5公里以下；此外，研究成果亦發現在新增10站雨量站時，克利金變異數下降幅度較高，增站效益較佳。Due to the geographical environment conditions, Taiwan frequently suffers from severe typhoons and rainfall events. These events cause not only flooding disasters in the plain area but also the debris flow disasters in mount ainous areas. Climate change further changes the rainfall patterns. Therefore, a reliable rainfall gauge observation network is important to support disaster prevention works. This study researches on improving rainfall gauge observation network. An experimental semi-variogram is used to fit different types of theoretical variogram models using collected rainfall data of typhoon and rainfall events from 1998 to 2013 in Taipei area. The appropriate theoretical variogram model is determined with the KAE and KRMSE methods. The analysis result shows that the observation range of rain gauge is about 5 km. Through the foregoing results and reviewing the number of rain gauges in Taipei area. After generating 5 by 5 km grids for Taipei area, we found 38 grids which have potential debris flow risk but lack of rain gauges. In order to assess the priority of rain gauges establishment, this research applies the sequential algorithm with the spatial property and weighting factors to evaluate the benefits for each potential new rain gauges. Kriging variance and spatial analysis are adopted for this assessment. After assessment, the distance between the potential debris flow area and rain gauge nearby can be less than 5 km. Furthermore, the results show that the value of kriging variance will decrease and also have better benefits when 10 rain gauges are established