Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19798
標題: 高動態範圍影像之可預測的資訊隱藏演算法
A Predictable Data Hiding Algorithm for High Dynamic Range Images.
作者: 卓弘文
Jhuo, Hong-Wun
關鍵字: Yao-Hsien Huang;可預測資訊隱藏;Yuan-Yu Tsai;多基底系統;高動態範圍影像;三階編碼
出版社: 資訊科學與工程學系所
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摘要: 
摘 要

在數位資訊發達的21世紀,資訊隱藏技術在秘密通訊以及資訊安全的課題中越來越受重視,由於高動態範圍影像所能表示之色彩範圍遠大於低動態範圍影像,使得高動態範圍影像日趨重要。因此本篇論文針對高動態範圍影像提出可預測的資訊隱藏演算法。
我們所提的第一個演算法為「使用多基底技巧於高動態範圍影像之資訊隱藏演算法」。演算法以Radiance RGBE的高動態範圍影像格式為掩護影像,將同一個像素中的Red、Green、Blue三個色彩頻道視為一個資訊嵌入單位。首先,使用者提供一個單位的嵌入位元量,我們的演算法根據此嵌入位元量決定所使用的多基底向量;接著,我們將二進位秘密訊息轉換為以多基底向量表示之多基底秘密訊息;最後,我們利用三階編碼與差值和餘數的關係,將多基底秘密訊息逐一嵌入到Red、Green、Blue三個色彩頻道,以增加訊息嵌入量。嵌入秘密訊息後,我們更利用基底同餘的特性,加或減去一個基底數值,來減少單一像素的變動量,藉此產出更佳品質的偽裝影像。實驗結果顯示:我們的演算法能對高動態範圍影像的單一個像素提供高達14~17位元的嵌入量;此外,當高動態範圍偽裝影像作色調映射處理後,所產出的低動態範圍偽裝影像,也仍可維持高於30 dB的PSNR數值。偽裝偵測實驗結果顯示:我們的演算法無從被統計學關係係數Pearson與Spearman及RS偽裝偵測方式偵測出影像內含秘密訊息。
我們所提的第二個演算法為「多基底系統於高動態範圍影像之預測機制」。我們提出一個期望變動量的預測機制,使得使用者無需實際將訊息嵌入,即能事先預知偽裝影像品質。為了增進預測的準確性,我們將秘密訊息分佈機率及影像特徵納入考量。透過數學分析的方法,我們將秘密訊息嵌入量、秘密訊息分佈機率、多基底訊息轉換、多基底演算法所可能造成的變動量、影像分佈特徵等關係列成一個數學函數表示矩陣。輸入不同的參數,並透過矩陣的計算,即可準確的計算出嵌入各種秘密訊息位元量下,偽裝影像所可能產生的期望變動量,並進而預知偽裝影像之品質。實驗結果顯示:不論秘密訊息分佈機率為何的情況下,我們的預測機制其誤差率最小僅0.0034%,最大也僅0.2162%。實驗數據佐證我們的預測機制具有極高的準確性。
本論文主要貢獻有下列六項:第一、改進多基底訊息轉換,使用三階編碼,進一步提升嵌入藏量。第二、改進尋找多基底的方式,可快速的找出適合的多基底向量。第三、提出一個應用於高動態範圍的資訊隱藏演算法,具有提供高藏量與低變形量之特性。第四、可準確計算出多基底演算法嵌入後的期望變動量,具有極高的準確度。第五、基底向量不易被破解,具備高安全性。第六、演算法具有盲擷取之特性。

Abstract
Data hiding has become an important research subject with the development of digital media where applications include digital right management, covert communications, information security, and medium annotation. As the availability of high-dynamic-range images increases, there is a growing demand to develop data hiding techniques for high-dynamic-range images in order to extend the coverage of applications.
This thesis proposes two data hiding algorithms for high-dynamic-range images. First, we consider a pixel encoding with the RGBE format as an embedding unit which consists of three primary red, green, and blue channels. This first proposed algorithm determines a multiple-base vector that can achieve the desired embedding capacity given by a user. Then, the binary secret message to be conveyed is converted into a multiple-base secret message using the multiple-base vector. Finally, we explore the advantage of triple coding and modulus operation for message embedding, allowing our scheme to increase the embedding capacity and produce a stego image with smaller distortion. Experimental results indicate that our algorithm produces a good quality of the stego image when the embedding capacity is as high as 14~17 bits per pixel. When operating the tone mapping, the tone-mapped stego image provides no visual difference with respect to the tone-mapped cover image where the PSNR value is over 30 dB. Our algorithm can resist the RS steganalysis attack and the histogram steganalysis attack which produces large Pearson and Spearman correlation coefficients.
The second scheme we propose is a prediction mechanism for high-dynamic- range image data hiding. This prediction mechanism takes into consideration the appearing probability of the secret bit “0” and “1” and the modulus features of high-dynamic-range images. This prediction scheme has a concise mathematical expression consisting of a product of four matrices. Each matrix deals with issues of the embedding capacity, the secret bit probability, the expected mean squared error, and the features of cover images. Given an appropriate parameter setting, our prediction scheme can estimate the mean squared error prior to practically any message. In addition, given a fixed cover image, we can report the expected image distortion under a variety of appearing probabilities for the secret bit. Our scheme provides the advantage of data hiding prediction which allows us to produce a high quality of stego image. Experimental results show that the proposed prediction scheme is accurate, the prediction error being in the range of 0.0034% and 0.2162%.
In conclusion, our work offers the following six contributions: (1) employing triple coding in order to increase the embedding capacity; (2) determining the desired multiple-base vector with efficiency; (3) presenting a data hiding algorithm with high capacity and high image quality for high-dynamic-range images; (4) predicting with high accuracy the expected mean squared error prior to real message embedding; (5) providing high embedding security that can resist RS and histogram steganalysis attacks; (6) sustaining the blind extraction scheme.
URI: http://hdl.handle.net/11455/19798
Appears in Collections:資訊科學與工程學系所

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