Digital Image Recovery and Multiple-Watermarking Techniques

博士 === 國立臺灣大學 === 電信工程學研究所 === 95 === The research topic of this paper is to integrate the digital image processing schemes and the watermarking techniques, and those methods will apply on the digital images and digital videos. The research topic includes three parts: (1) image recovery, colorizatio...

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Main Authors: Yi-Chong Zeng, 曾易聰
Other Authors: Soo-Chang Pei
Format: Others
Language:en_US
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/94534920729538248617
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description 博士 === 國立臺灣大學 === 電信工程學研究所 === 95 === The research topic of this paper is to integrate the digital image processing schemes and the watermarking techniques, and those methods will apply on the digital images and digital videos. The research topic includes three parts: (1) image recovery, colorization and enhancement, (2) multiple-watermarking techniques, and (3) the integration of image recovery and multiple-watermarking techniques. The abstracts of all chapters are described below: Chapter 1 – Image Recovery The lacuna texture synthesis is proposed for the virtual restoration of ancient Chinese paintings and digital images. Lacuna texture synthesis is a patching method, which uses the Markov Random Field (MRF) model. We eliminate the undesirable patterns, such as stains, crevices, and artifacts, and the algorithm fills the lacuna regions with the appropriate textures. The proposed scheme not only maintains a complete shape, but also prevents the edge disconnection in the final results. Chapter 2 – Visible Watermark Removal In this chapter, an image recovery algorithm for removing visible watermarks is presented. Independent component analysis (ICA) is utilized to separate source images from watermarked and reference images. Three independent component analysis approaches and five different visible watermarking methods are examined in our study. The experimental results will show that visible watermarks are successfully removed, and that the proposed algorithm is independent of both the adopted ICA approach and the visible watermarking method. Moreover, several watermarked images sourced from various websites are removed the watermarks successively. Chapter 3 – Image Colorization In the past, the artists adopted the black ink to represent various sights and objects in Chinese ink-and-wash, such as, mountain scenery, waterscape, animals, plants, etc. This chapter will introduce an effective method to colorize the Chinese ink-and-wash paintings. The proposed method not only takes fewer computing time than the conventional method, but it also can preserve the soft-gradual tone in the ink-and-wash paintings, such as, water-flowing, smog, cloud, waterfall, and shadow etc. Chapter 4 – Image Enhancement We will introduce the weighted histogram separation (WHS) in this chapter, which is presented to enhance the high dynamic range images. The property of weighted histogram separation situates between the successive mean quantization transform and the histogram equalization. Additionally, the proposed method is further applied to the local enhancement, which is termed as the adaptive weighted histogram separation (AWHS). Chapter 5 – Spatial Domain Multiple-watermarking Algorithm The objective of our study in information security is to develop a multiple watermarks embedding and extraction algorithm, which is called as spatial domain multiple-watermarking algorithm. This algorithm is one kind of quantization index modulation, it can impose bi-watermark or tri-watermark on the host image. Furthermore, the extracted watermarks not only are exploited to detect the tampered areas, but it is also used for attack classification and attack identification. Chapter 6 – Dual Domain Bi-watermarking Algorithm A dual domain bi-watermarking algorithm embeds bi-watermark into the host image in discrete-cosine-transform domain (DCT), and it is the extension of the spatial domain bi-watermarking algorithm. However, the bi-watermark can be extracted from both spatial domain and DCT domain. By the same token, two separated watermarks from the extracted bi-watermark have different capability for various compression rates, and they also reveal the different robustness against the global and the regional attacks. Chapter 7 – 2.5 Domain Tri-watermarking Algorithm In this chapter, we will introduce an integration of dual domain bi-watermarking algorithm and visual cryptography, which is named as 2.5 domain tri-watermarking algorithm (2.5D-TW). This algorithm implements tri-watermark embedding in discrete-cosine-transform domain (DCT) for video protection, but the tri-watermark can be extracted from both spatial domain and DCT domain. Three separated watermarks from the extracted tri-watermark reveal the different robustness against various attacks. According to the bit error rates of those three watermarks, the algorithm even identifies whether the attack is occurred in spatial domain or in temporal domain for video. Chapter 8 – Integration of Image Recovery and Watermarking Algorithm The key of this chapter is to integrate the image recovery scheme and the watermarking technique. The spatial domain bi-watermarking algorithm is used to add the halftone of downscaled host image into the host image. After extracting the bi-watermark from the covered image, the bi-watermark is restored to the gray-scale image using the proposed inverse halftoning, which utilizes the linear programming and quadratic programming. Furthermore, the bi-watermark is not only exploited to detect the tampered areas without prior data, but it also can be applied to recover the tampered areas in the tampered image. Chapter 9 – Linear Programming and Its Applications In 1736, the great mathematician Leonhard Euler published a paper to solve the problem of seven bridges of Königsberg, and he translated it into the graph theory problem. This study is the well-known Euler circuit problem. Here, we solve non-Euler circuit problem using mix-integer linear programming, which transforms the non-Euler circuit to the Euler one. In addition, the binary integer programming is exploited to determine the edge direction. The experimental results will show that the proposed scheme can be applied to the route planning, the continuous line drawing and the real-object production. Chapter 10 – Conclusions and Future Works Consequently, we will summarize the previous researches and describe the possible improvement and applications in the future works.
author2 Soo-Chang Pei
author_facet Soo-Chang Pei
Yi-Chong Zeng
曾易聰
author Yi-Chong Zeng
曾易聰
spellingShingle Yi-Chong Zeng
曾易聰
Digital Image Recovery and Multiple-Watermarking Techniques
author_sort Yi-Chong Zeng
title Digital Image Recovery and Multiple-Watermarking Techniques
title_short Digital Image Recovery and Multiple-Watermarking Techniques
title_full Digital Image Recovery and Multiple-Watermarking Techniques
title_fullStr Digital Image Recovery and Multiple-Watermarking Techniques
title_full_unstemmed Digital Image Recovery and Multiple-Watermarking Techniques
title_sort digital image recovery and multiple-watermarking techniques
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/94534920729538248617
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spelling ndltd-TW-095NTU054350022015-12-11T04:04:49Z http://ndltd.ncl.edu.tw/handle/94534920729538248617 Digital Image Recovery and Multiple-Watermarking Techniques 數位影像修復與多重浮水印技術 Yi-Chong Zeng 曾易聰 博士 國立臺灣大學 電信工程學研究所 95 The research topic of this paper is to integrate the digital image processing schemes and the watermarking techniques, and those methods will apply on the digital images and digital videos. The research topic includes three parts: (1) image recovery, colorization and enhancement, (2) multiple-watermarking techniques, and (3) the integration of image recovery and multiple-watermarking techniques. The abstracts of all chapters are described below: Chapter 1 – Image Recovery The lacuna texture synthesis is proposed for the virtual restoration of ancient Chinese paintings and digital images. Lacuna texture synthesis is a patching method, which uses the Markov Random Field (MRF) model. We eliminate the undesirable patterns, such as stains, crevices, and artifacts, and the algorithm fills the lacuna regions with the appropriate textures. The proposed scheme not only maintains a complete shape, but also prevents the edge disconnection in the final results. Chapter 2 – Visible Watermark Removal In this chapter, an image recovery algorithm for removing visible watermarks is presented. Independent component analysis (ICA) is utilized to separate source images from watermarked and reference images. Three independent component analysis approaches and five different visible watermarking methods are examined in our study. The experimental results will show that visible watermarks are successfully removed, and that the proposed algorithm is independent of both the adopted ICA approach and the visible watermarking method. Moreover, several watermarked images sourced from various websites are removed the watermarks successively. Chapter 3 – Image Colorization In the past, the artists adopted the black ink to represent various sights and objects in Chinese ink-and-wash, such as, mountain scenery, waterscape, animals, plants, etc. This chapter will introduce an effective method to colorize the Chinese ink-and-wash paintings. The proposed method not only takes fewer computing time than the conventional method, but it also can preserve the soft-gradual tone in the ink-and-wash paintings, such as, water-flowing, smog, cloud, waterfall, and shadow etc. Chapter 4 – Image Enhancement We will introduce the weighted histogram separation (WHS) in this chapter, which is presented to enhance the high dynamic range images. The property of weighted histogram separation situates between the successive mean quantization transform and the histogram equalization. Additionally, the proposed method is further applied to the local enhancement, which is termed as the adaptive weighted histogram separation (AWHS). Chapter 5 – Spatial Domain Multiple-watermarking Algorithm The objective of our study in information security is to develop a multiple watermarks embedding and extraction algorithm, which is called as spatial domain multiple-watermarking algorithm. This algorithm is one kind of quantization index modulation, it can impose bi-watermark or tri-watermark on the host image. Furthermore, the extracted watermarks not only are exploited to detect the tampered areas, but it is also used for attack classification and attack identification. Chapter 6 – Dual Domain Bi-watermarking Algorithm A dual domain bi-watermarking algorithm embeds bi-watermark into the host image in discrete-cosine-transform domain (DCT), and it is the extension of the spatial domain bi-watermarking algorithm. However, the bi-watermark can be extracted from both spatial domain and DCT domain. By the same token, two separated watermarks from the extracted bi-watermark have different capability for various compression rates, and they also reveal the different robustness against the global and the regional attacks. Chapter 7 – 2.5 Domain Tri-watermarking Algorithm In this chapter, we will introduce an integration of dual domain bi-watermarking algorithm and visual cryptography, which is named as 2.5 domain tri-watermarking algorithm (2.5D-TW). This algorithm implements tri-watermark embedding in discrete-cosine-transform domain (DCT) for video protection, but the tri-watermark can be extracted from both spatial domain and DCT domain. Three separated watermarks from the extracted tri-watermark reveal the different robustness against various attacks. According to the bit error rates of those three watermarks, the algorithm even identifies whether the attack is occurred in spatial domain or in temporal domain for video. Chapter 8 – Integration of Image Recovery and Watermarking Algorithm The key of this chapter is to integrate the image recovery scheme and the watermarking technique. The spatial domain bi-watermarking algorithm is used to add the halftone of downscaled host image into the host image. After extracting the bi-watermark from the covered image, the bi-watermark is restored to the gray-scale image using the proposed inverse halftoning, which utilizes the linear programming and quadratic programming. Furthermore, the bi-watermark is not only exploited to detect the tampered areas without prior data, but it also can be applied to recover the tampered areas in the tampered image. Chapter 9 – Linear Programming and Its Applications In 1736, the great mathematician Leonhard Euler published a paper to solve the problem of seven bridges of Königsberg, and he translated it into the graph theory problem. This study is the well-known Euler circuit problem. Here, we solve non-Euler circuit problem using mix-integer linear programming, which transforms the non-Euler circuit to the Euler one. In addition, the binary integer programming is exploited to determine the edge direction. The experimental results will show that the proposed scheme can be applied to the route planning, the continuous line drawing and the real-object production. Chapter 10 – Conclusions and Future Works Consequently, we will summarize the previous researches and describe the possible improvement and applications in the future works. Soo-Chang Pei 貝蘇章 2007 學位論文 ; thesis 246 en_US