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A Study of High Capacity Steganographic Algorithms for High Dynamic Range Images Based on Human Visual Sensitivity
|關鍵字:||high dynamic range images;高動態範圍影像;steganography;high capacity;high visual quality;human visual sensitivity;adaptability;資料隱藏技術;高容量;高視覺品質;人類視覺敏感度;可適應性||出版社:||資訊科學與工程學系所||引用:||[Adel1982] E. H. Adelson, “Saturation and Adaptation in the Rod System,” Vision Research, 22:1299-1312, 1982. [Adob2005] Adobe company, The AdobeRGB(1998) Specification, 2005, (http://www.adobe.com/digitalimag/adobergb.html). [Alat2004] M. Alattar, “Reversible Watermark Using the Difference Expansion of a Generalized Integer Transform,” IEEE Transactions on Image Processing, Vol. 13, pp. 1147-1155, 2004. [Ashi2002] M. Ashikhmin, “A Tone Mapping Algorithm for High Contrast Images,” Rendering Techniques 2002 (13th Eurographics Workshop on Rendering), pp. 145-156, 2002. [Ashi2006] M. Ashikhmin and J. Goyal, “A Reality Check for Tone-mapping Operators,” ACM Transactions on Applied Perception, Vol. 3, No. 4, pp. 399-411, 2006. [Bant2006] F. Banterle, P. Ledda, K. Debattista, and A. 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High dynamic range images demonstrate significant advantages over the low dynamic range images. With the popularity of the Internet, steganography becomes more important as a means of concealing information from prying eyes before ultimately reaching its intended destination. This thesis presents two steganographic algorithms, which utilize a high dynamic range image as the cover image to embed secret message to become the stego image that can be applied for the covert communication.
The first algorithm we propose is a high capacity and quality steganographic algorithm for high dynamic range images. Given an input high dynamic range image with the RGBE format, our algorithm considers the luminance distribution characterized in the cover image and the intensity difference existed in the neighboring pixels. The algorithm estimates the overall amount of message that can be embedded in a single pixel. Then, different red, green, and blue channels are assigned to certain parts of the overall message based on the color sensitivity inherent from the human vision. Finally, we present an original embedding technique to embed the payloads at each color channel. This allows our algorithm to be able to embed a great number of secret messages, yet producing the stego high dynamic range image with high visual quality.
The second algorithm we propose is a steganographic algorithm for high dynamic range images based on human visual sensitivity. This algorithm improves the estimation step encountered in the first algorithm to determine the potential embedding capacity. In particular, we analyze the luminance distribution in the cover image and determine a number of appropriate levels into which secrete message can be embedded accordingly. Once the maximal and minimal capacity that can be embedded in a pixel are settled, we proceed on non-linear mapping of these two extremes to various luminance levels being determined. This allows our algorithm to estimate the possible embedding capacity using more precise information for the human visual sensitivity. As a consequence, the embedding capacity can be increased significantly.
Experimental results show that, on average, the embedding capacity can achieve to the magnitude of 11.6~13.5 bits per pixel when using our first algorithm. In addition, we can increase the capacity to 12.9~20.3 bits per pixel when employing the second algorithm. To the best of our knowledge, this capacity is the highest in the literature of steganography for high dynamic range images.
Our two algorithms have the following characteristics; namely, (1) appropriate to characteristics of high dynamic range images, (2) extremely high capacity, (3) high visual quality, (4) adaptability based on the human visual sensitivity, (5) the original embedding technique, (6) secure steganography, and (7) belonging to the blind detection scheme. The major contribution of our thesis includes the steganographic algorithms we proposed contain the originality, it has the highest capacity in the literature, and the algorithm makes full use of the human visual characteristics.
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