Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19662
標題: 植基於人類視覺靈敏度之高視覺品質影像藏密學技術之研究
A Study of High Visual Quality Steganographic Schemes Based on Human Visual Sensitivity
作者: 吳男益
Wu, Nan-I
關鍵字: Information hiding, data hiding, adaptive;資訊隱藏技術;human visual sensitivity;imperceptibility;藏密學技術;可適應性;人類視覺靈敏度;不可察覺性
出版社: 資訊科學與工程學系所
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摘要: 
影像藏密學技術(image steganography)是隱匿式通訊方法之一,它主要是利用一張影像來當作掩護媒介,透過將秘密訊息藏匿在影像中的手法來躲避潛藏性的攻擊(potential attacker)。本論文主要研究方向著重於符合人類視覺靈敏的可適應性灰階影像藏密學技術之研究。
首先,我們植基於像素差值法(pixel-value differencing)與模數函數運算(modulus function)之上,提出一個具有高品質效果的可適應性藏密學技術。此方法主要是利用像素差值技術來決定每一個像素對的訊息可嵌入隱藏量,像素差值法其特色為基於人類視覺靈敏度來可適應性的分配訊息隱藏量大小。我們是用利模數函數運算來調整像素對的之餘數以達到記錄秘密訊息的目的,此方式也可以克服falling-of-boundary的問題,竟而達到減少影像失真的效果。
接著,提出一個以區塊式為主的可適應性藏密學技術。此方法是利用標準差概念來分析掩護影像區域複雜度,並且,每一個區塊的隱藏量也是取決於該區塊的標準差大小。因為標準差值較高的影像子區塊,在訊息嵌入之後,具備能容忍較大的像素變動量,因此,我們藏較多的訊息量於此類型區塊中。 我們所提的新方法尚具備一個重要的優點,即能在訊息未嵌入之前,依照使用者給定的容量需求來預估偽裝影像所對應的PSNR值。
最後,植基於像素差值法與基底分解技術(base decomposition),我們提出一個具有非常高品質偽裝影像的可適應性藏密學技術。在此方法中,為了可以降低在嵌入訊息之後的視覺品質破壞,我們有改善原始PVD技術在像素對隱藏量分配的機制。更進一步地,我們提出一個基底分解技術,可以在訊息嵌入時所需的像素變動量上達到一個最小化作用。在新方法的效能的評估上,我們使用了三種影像品質評估技術,以証明新方法的可行性是非常地高的。
由大量的實驗所得的結果証明本論文所提的三個可適應性藏密學方法,擁有很好的效能。我們的技術具有盲擷取與低計算複雜度的特性,因此,新方法在實際應用方面其實用性是非常高的。實驗結果也提供充份的証據,証明我們所提的方法其效能確實優於同類型的可適應藏密學技術,相信本論文所提的新方法提供了在影像藏密學研究方面具有重要的貢獻。

Image steganography is one of the covert communication methods which uses an image as the cover medium in order to hide the truth from potential attackers that secret messages are hidden within the image. In this thesis, we examine closely adaptive steganographic techniques for grayscale images based on human visual sensitivity.
First, we propose a high quality adaptive steganographic method based on pixel-value differencing and modulus function. In this scheme, the pixel-value differencing (PVD) method is utilized to determine the payload that can be embedded for each pixel pair. The PVD scheme leads to adaptive message embedding for the cover image based on human visual sensitivity. We adjust the remainder of a pixel pair in order to conceal the secret data based on the modulus function. We also present an algorithm that solves the falling-of-boundary problem, resulting in reducing the image distortion introduced by our data hiding scheme.
Second, we present a block-based adaptive steganographic algorithm which employs the standard deviation concept in order to analyze the local complexity of the cover image. In this scheme, the secret data to be embedded within a block is determined by standard deviation. We hide more secret data into a block with a higher standard deviation because this block is more tolerant to the pixel variation caused by the hidden data. A key advantage of this scheme is that it is capable of predicting the corresponding PSNR value to the desired payload given by users.
Finally, we propose an adaptive scheme that is able to produce a very high quality stego image using the pixel-value differencing and base decomposition techniques. In this scheme, we improve upon the original version of the PVD scheme by determining the payload degree for each pixel pair. This allows us to reduce the visual quality degradation after the data embedding. Further, we present a base decomposition system which minimizes the pixel variation encountered because of the hidden message. We adopt three image quality metrics in order to evaluate the feasibility of our new scheme. We conduct a number of experiments to evaluate the proposed three schemes.
Experimental results demonstrate that all three adaptive schemes offer good performance. Our schemes have a blind manner and low computation complexity, demonstrating high practicability for real applications. Experimental results provide evidence that the proposed adaptive stenographic algorithms outperform our counterparts. We believe these methods make a substantial contribution to the field of image steganography.
URI: http://hdl.handle.net/11455/19662
其他識別: U0005-2907200920303400
Appears in Collections:資訊科學與工程學系所

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