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研究生:黎世琦
研究生(外文):Shih-Ci Li
論文名稱:使用權重技巧的高品質偽裝學演算法
論文名稱(外文):A Very High Quality Steganographic Algorithm Using a Novel Weighted Modulus Technique
指導教授:王宗銘王宗銘引用關係
學位類別:碩士
校院名稱:國立中興大學
系所名稱:資訊網路多媒體研究所
學門:電算機學門
學類:軟體發展學類
論文種類:學術論文
畢業學年度:97
語文別:中文
論文頁數:67
中文關鍵詞:高視覺品質偽裝學資訊隱藏權重模數技巧灰階影像彩色影像人類視覺敏感度
外文關鍵詞:high visual qualitysteganographyweighted modulus techniquegray scale imagescolor imageshuman visual sensitivity
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如何提升偽裝影像品質與增加嵌入量一直是資訊隱藏探討的重要課題。本文提出使用權重模數技巧的高品質資訊隱藏演算法。藉由引進權重模數的觀念,發展之演算法不僅能滿足使用者之嵌入量需求,亦可提升偽裝影像之視覺品質。我們所提的第一個演算法為「使用權重技巧的高品質灰階影像偽裝學演算法」。當使用者決定嵌入量需求後,以三個掩護像素為一組嵌入單位,將對應之掩護像素乘上我們求出的可用權重值,計算出其權重和後取其模數。接著根據欲嵌入之訊息與求得之模數間之差值,決定如何變動嵌入單位之個別像素數值,藉此達到嵌入秘密訊息之目的。我們的演算法可在遂行實際之訊息嵌入前,就預先評估所可能引起之變動量。藉此評估,得以滿足使用者之嵌入量需求,同時產生具有極高品質的偽裝影像。實驗結果顯示:當每嵌入單位之嵌入量為3的倍數位元時,例如3、6、9、12位元,我們的偽裝影像品質優於現有文獻之結果。此外,本文提出的演算法也求出非屬上述嵌入量之可用權重,亦可藉由這些可用權重,順利嵌入相對應數量之秘密訊息,此為文獻上現存之嵌入演算法所無法達到的。實驗結果顯示我們演算法的成效優於文獻之演算法,確實可產生高品質之偽裝影像。
我們將技術拓展至彩色影像,提出「使用權重模數技巧之彩色影像資訊隱藏演算法」。此處以單一像素之紅色、綠色、藍色三個色彩頻道為一個資訊嵌入單位。我們先估算各權重值所引起之變動量;接著,將變動量最大的權重數值對應至藍色頻道;相對的,將變動量最小的權重數值對應至綠色頻道。此種頻道對應之調整得以讓我們的演算法產生高品質的偽裝影像,並符合人眼視覺對色彩改變的特性。與現有文獻比較下,當單位像素嵌入量為8位元(8 bpp)時,我們的方法可產生高達43.1787 dB之偽裝影像,優於文獻上所能達到最佳的41.8 dB品質。在相同品質或甚至更優之影像品質下,我們的演算法可提高將近0.5 bpp的資訊嵌入量。最後,我們也使用文獻之方法模擬其他嵌入量之結果。實驗結果證實:在所有模擬之嵌入量下,我們演算法均能產生更佳的偽裝影像品質,優於模擬文獻方法之結果。
本論文研究具有以下下列八大貢獻,分別為(1)極佳的視覺品質、(2)符合使用者基本需求之嵌入量、(3)優於現存文獻之結果、(4)切合彩色影像單一像素三頻道之嵌入特性、(5)預先評估演算法的變動量、(6)滿足更精細嵌入量之需求、(7)高安全性與(8)盲擷取性。
An important topic of stenography is, without question, how to enhance stego image quality and increase capacity. This thesis proposes a steganographic algorithm using a weighted modulus technique. This allows us to meet the demand of the embedded capacity from the user, and also to upgrade the quality of the stego image.
The first algorithm we propose is a high quality steganographic algorithm for gray scale images. Once a desired capacity is given by the users, our algorithm employs an effective weight to embed the secret message into the cover image. Accordingly, we use a group of three cover pixels for the embedded units corresponding to the weight; furthermore, we can receive the modulus by calculating the product sum of the weight and the cover pixels. As a consequence, we can change the pixel value of the embedded units to embed messages through the difference between the modulus and the message. Therefore, we can produce a high quality stego image and fulfill the requirement of capacity at once by estimating the possible pixel variation encountered due to the hidden message. Experimental results show that our scheme outperforms any other literature when the capacity of the embedded unit is 3、6、9 and 12 bits. In addition, our algorithm can also obtain a capacity such as 4、5、7、8、10、11 bits, etc., with distinguished results. To the best of our knowledge, this result offers an achievement which has not yet been presented in the current literature.
This study proposes another high quality steganographic algorithm for color images by expanding the weighted modulus technique. We regarded the three color channels, namely red, green and blue, as an embedded unit. In the first place, we must obtain the variation from each weight value. Subsequently, we match the weight value which causes the most variation with blue channel, but we match the green channel with the weight value which causes the least variation relatively. Therefore, our algorithm produces a stego image with high quality based on human vision sensitivity through the adjustment of the weight value and color channels. Experimental results show that the quality of the stego image produced by our algorithm can achieve up to a magnitude of 43.1787 dB, which is better than the reference literature which only attains 41.8 dB when embedding a capacity of 8 bits per pixel. Furthermore, we can increase the capacity almost 0.5 bits per pixel under the same or even higher quality of stego image. In addition, we simulate the capacity with the proposed method in the reference literature. As a result, our algorithm produces a stego image that is higher in quality than any other algorithm under all amounts of capacity.
This thesis has the following eight major contributions: (1) extremely high visual quality, (2) meets the demand of embedded capacity from user, (3) results superior to existing literature, (4) appropriate to characteristics of color images, (5) predicts the variation of the algorithm, (6) achieves higher precision of capacity, (7) secures steganography and (8) belongs to the blind detection scheme.
致 謝 ……………………………………………………………………… i
摘 要 ……………………………………………………………………… ii
Abstract ……………………………………………………………………… iv
目 次 ……………………………………………………………………… vi
圖 目 次 …………………………………………………………………… viii
表 目 次 …………………………………………………………………… ix

第一章 緒論 1
1.1 研究動機 …………………………………………………………… 1
1.2 研究目的 …………………………………………………………… 2
1.3 論文架構 …………………………………………………………… 3

第二章 背景與相關文獻回顧 4
2.1 灰階影像上的資訊隱藏技術 ………………………………………… 4
2.2 彩色影像上的資訊隱藏技術 ………………………………………… 6
2.3 相關研究分析與心得 ……………………………………………… 13

第三章 使用權重技巧的高品質灰階影像偽裝學演算法 15
3.1 決定嵌入權重值 ……………………………………………………… 15
3.2 可用權重分析 ………………………………………………… 20
3.3 灰階影像嵌入與擷取演算法 ………………………………………… 23
3.3.1 演算法概要 ……………………………………………………… 24
3.3.2 權重值演算法嵌入程序 ………………………………………… 25
3.3.3 權重值演算法擷取程序 ………………………………………… 28
3.4 理論分析與實驗結果 .....………………………………………… 28
3.4.1 理論數據並與OPAP比較 ………………………………………… 29
3.4.2 實驗結果並與OPAP比較 ………………………………………… 30
3.5 小結 ………………………………………………………………… 35

第四章 使用權重模數技巧之彩色影像資訊隱藏演算法 36
4.1 決定嵌入權值與變動量分析 ……………………………………… 36
4.2 彩色影像嵌入與擷取演算法 ……………………………………… 38
4.2.1 演算法概要 …………………………………………………… 39
4.2.2 權重值演算法嵌入與擷取程序 ……………………………… 40
4.3 理論分析與實驗結果 ……………………………………………… 43
4.3.1 理論分析並與YU等人提出之方法比較 ……………………… 44
4.3.2 實驗結果並與YU等人提出之方法比較 ……………………… 45
4.4 小結 ………………………………………………………………… 51

第五章 結論與未來工作 53
5.1 結論 ………………………………………………………………… 53
5.2 未來工作 …………………………………………………………… 54

參考文獻 …………………………………………………………………… 56
中英對照表 ………………………………………………………………… 64
英中對照表 ………………………………………………………………… 66
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