Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19607
標題: 可回復式灰階及高動態範圍影像資訊隱藏演算法之研究
A Study of Reversible Data Hiding Algorithms for Grayscale and High Dynamic Range Images
作者: 黃姵甄
Huang, Pei-Chen
關鍵字: grayscale images;灰階影像;low dynamic range images;high dynamic range images;reversible data hiding;histogram modification;difference expansion;adaptability;high embedding efficiency;低動態範圍影像;高動態範圍影像;可回復式資訊隱藏;直方圖技術;差值擴張技術;可適應性;高嵌入效率
出版社: 資訊科學與工程學系所
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摘要: 
可回復式資訊隱藏技術為資訊隱藏技術與資訊安全開創一個新的世代。所謂可回復性,即從偽裝媒體中取出秘密資訊後仍可完整的重建原始掩護媒體。可回復式資訊隱藏技術之應用,包含掩護認證(Cover Authentication)、內容完整性驗證(Contents Integrity Verification)、秘密通訊(Covert Communication)、影像編碼(Image Coding)或視訊編碼(Video Coding)等。

本文研究可回復式資訊隱藏演算法。首先,我們提出一個應用於灰階影像上的可回復式資訊隱藏演算法。此法先將掩護影像區塊化,藉此將區塊分類,並針對特定類型的區塊,利用我們所提出之區塊差值擴張技術,將秘密資訊嵌入其中。透過區塊化的概念,可以有效地降低額外資訊量,提高資訊嵌入量,維持低失真性,進而產生具有高淨嵌入量且高品質特性的偽裝影像。經量化顯示:每一個像素之淨嵌入量可高達0.66位元,PSNR值能維持在34dB以上,具有極佳的視覺品質。

現存以差值擴張為基礎的可回復式資訊隱藏技術,通常具有較高嵌入量,但此法必須事先定義合理的門檻值,以便能控制影像之失真程度。因此,如何決定最佳門檻值是值得探究的議題。據此,我們提出一個高嵌入效率評估門檻值技術,能夠依使用者之需求,自動選擇最佳門檻值,使得偽裝影像能具有最高的嵌入效率,此代表所嵌入之資訊量與所導致的影像失真之間達到一個最佳的平衡狀態。此外,透過我們所提出的技術所決定之最佳門檻值,可以滿足使用者對高淨嵌入量或高視覺品質之需求,我們的技術具備相當大的彈性空間。

高動態範圍影像,憑藉著補足大量的亮度資訊用以提高數位影像的品質,能呈現出真實世界的豐富色彩,符合人眼視覺的感官,亦必將成為數位多媒體物件的新標竿。據此,我們提出高動態範圍影像可回復式資訊隱藏演算法。就我們所知,此為文獻上之首創。我們的演算法透過Radiance RGBE格式獨有的屬性,計算各色彩頻道相鄰數值的差異程度,並考量相鄰像素中E值的分佈情況,以可適應性的方式將資訊嵌入至每一個色彩頻道的差值中。我們的演算法有效地提高資訊嵌入量:單次的資訊嵌入下,每像素之淨嵌入量可達0.13~0.63位元,其NRMSE數值為0.05%~0.83%;經過色調再生處理後,偽裝影像之PSNR數值仍可維持在39dB以上,具備極佳的視覺品質。

為了達到更高的嵌入量及視覺品質,我們提出第二個應用於高動態範圍影像的可回復式資訊隱藏演算法。我們在這個改進的演算法中增加一個估算步驟,並透過估算後所計算出額外資訊量及影像原始可提供之嵌入量,來決定各色彩頻道內相鄰數值間差值所能嵌入之資訊量,資訊嵌入技術包含可適應性嵌入與低失真性嵌入兩種技術。我們的演算法透過預估方式,大幅降低額外資訊量,故能提升資訊嵌入量,降低所引起的影像失真性。實驗結果顯示:在多次嵌入時,演算法仍可回復高動態範圍掩護影像之原始像素值,不致產生任何錯誤;平均淨嵌入量為每像素1.76位元,其平均NRMSE數值為1.06%;經過色調再生處理後,三個色彩頻道的平均PSNR數值仍能維持在30.78dB以上。若單次嵌入,則每像素之淨嵌入量最高可達0.63位元,其NRMSE數值為0.13%,經過色調再生處理後,其PSNR數值為51.89dB。

總結本文,本研究具有下列四大貢獻:(1)我們演算法提供現存技術中最高的淨嵌入量、(2)現存技術中最少需要記錄之額外資訊、(3)提出高嵌入效率評估門檻值技術以決定最佳門檻值、(4)首創於高動態範圍影像上發展效果優異之可回復式資訊隱藏演算法。

Reversible data hiding has marked a new epoch for data hiding and information security. Being reversible, the cover image can be recovered from the stego image completely after the secret message being extracted. The potential applications for this technique include authentication, content integrity verification, cover communication, and image coding or video coding.

We present a reversible data hiding algorithm for grayscale images. First, a cover image is partitioned into a number of blocks. Then, we classify these blocks into a number of different categories where blocks in a category contain similar features. The block classification produces a number of candidate blocks that are able to embed a variety of secret messages. Finally, we exploit the block-based difference expansion technique on specific candidate blocks in order to embed the secret message.

This approach effectively allows us to reduce the size of the extra information and to embed large amounts of secret messages. In addition, our scheme can lower the pixel variation due to the hidden message, generating a stego image with a high pure payload and high visual quality. Experimental results show that, our algorithm achieves the pure payload for up to 0.66 bits per pixel (bpp). In addition, the stego image has achieved the peak signal-to-noise ratio (PSNR) higher than 34 dB.

In recent literature, quite a few reversible data hiding algorithms have been proposed. Difference expansion techniques have attracted a lot of attention for high embedding capacity. The scenario behind the difference expansion is to determine an appropriate threshold to avoid degrading the image quality. In this thesis, we present a threshold evaluation technique for achieving high embedding efficiency. Our scheme is able to automatically determine a suitable threshold which satisfies a user's demand for capacity or image quality. In addition, our evaluation technique can derive the optimal threshold that can be used for secret message embedding. Using this optimal threshold ensures that a cover image reaches the highest embedding efficiency representing the best equilibrium state between the embedding capacity and the image quality.

High dynamic range (HDR) images have been proposed in the computer graphics community to effectively represent luminance and colors of the real world. In this thesis, we present a reversible data hiding algorithm for high dynamic range images. To the best of our knowledge, we are the first to present such an algorithm in the literature. Given an HDR image encoded with the RGBE format, we consider the differences of the neighboring pixels in the R, G, and B channels and the differences of the neighboring pixels in the exponent channel. This leads to embedding a dynamic range of the secret message, achieving the manner of adaptive embedding. Experimental results show that our algorithm provides a pure payload in the range of 0.13~0.63 bits per pixel (bpp). Given such a high pure payload, our algorithm can still produce a stego image with high visual quality. The normalized root mean squared error (NRMSE) is in the range of 0.05%~0.83%, and the peak signal-to-noise ratio (PSNR) between the stego and cover HDR images after the tone mapping process is over 39 dB.

We also present a reversible data hiding algorithm that achieves high embedding capacity and high visual quality for high dynamic range images. We derive an evaluation step in the proposed algorithm to determine the embedding capacity based on the differences of the neighboring pixels in the R, G, and B channels. The embedding technique includes both approaches for adaptive embedding and low-distortion embedding. Our algorithm decreases the extra information that has to be held for reversibility. As a consequence, our scheme increases the embedding capacity significantly, yet the image quality distortion remains as small as possible. Experimental results show that our algorithm provides an average pure payload for up to 1.76 bits per pixel (bpp) using multiple planes of the secret message embedding. Our scheme produces the stego image with high visual quality. The normalized root mean squared error (NRMSE) reaches to 1.06 %, and the peak signal-to-noise ratio (PSNR) between the stego and cover HDR images after the tone mapping process is over 30.78 dB. In contrast, if we employ only one plane of the embedding, our algorithm produces a pure payload of 0.63 bits per pixel (bpp), 1.06% for the NRMSE, and the PSNR of 55.11 dB.

In summary, the major contribution of our thesis contends that we have achieved the highest pure payload and the smallest amount of extra information in the literature. In addition, we present a novel threshold evaluation technique for high embedding efficiency, leading to deriving the optimal threshold which satisfies a user's demand. Finally, we present the first reversible data hiding algorithm for high dynamic range images, achieving significantly high embedding capacity.
URI: http://hdl.handle.net/11455/19607
其他識別: U0005-1407200914515000
Appears in Collections:資訊科學與工程學系所

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