A Variation Prediction Scheme and an HDR Image Data Hiding Algorithm Using a Weighted Modulus Technique
| Autor: | Cheng-Ming Su, 蘇建銘 |
|---|---|
| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 High dynamic range images are able to store a greater dynamic range of luminance in order to more accurately represent the range of intensity levels found in real scenes. This thesis presents a dynamic approach for data hiding, and introduces a prediction scheme based on the weighted modulus embedding technique. We provide a dynamic pixel adjustment approach for data hiding using the weighted modulus embedding technique. In particular, we consider the R, G, and B channel of the Radiance RGBE encoding format as an embedding unit. In contrast to a static approach, our algorithm alters pixels dynamically when they are encountered with an overflow or underflow problem. This allows our method to reduce the pixel variation due to message embedding and produce a stego image that has less distortion than the static approach. In addition, our dynamic approach maintains the integrity of the RGBE image encoding. Consequently, we are able to produce a stego image which causes no suspicion when the legality of the image encoding is inspected. Experimental results show that the dynamic adjustment can reduce 61%~91% of the number of pixels and decrease 0.8%~4.39% the image variation in comparison with the static approach. Tone-mapped images perform with a good visual quality where the PSNR values are over 30 dB when each pixel is conveyed with 15 bits of secret message. Our data hiding algorithm can resist the RS steganalysis attack and provides high correlation coefficients between the pixel histograms of cover and stego images. Our algorithm provides benefits of high embedding capacity, high image quality, and high security. The second algorithm we present is a prediction scheme that is able to foresee the expected mean squared error. Our scheme considers three factors including the probability appearance of the secret bit “0” and “1,” the embedding capacity, and the medium features of the high dynamic range images. Specifically, we present a mathematical analysis and we compute the expected mean squared error by simply multiplying four independent matrices. Given a cover high dynamic range image and the probability of the secret bits, our scheme can forecast the mean squared error prior to the real message embedding. Given a range of probability appearance, our mechanism can suggest the best values with this range for a specific cover image in order to produce the stego image that has the smallest pixel variation. We include a variety of high dynamic range images including low, middle, and high keys when conducting an experiment. The experimental results show that our scheme reveals a high accuracy of prediction, the error rates being in the range of 0.01%~0.59%. The accuracy is preserved even when each pixel is concealed with 15 bits of secret messages. Tone-mapped images produced by two different tone mapping algorithms demonstrate that the PSNR values are over 30 dB, and produce a good visual quality of stego images. In conclusion, this study provides three contributions: the dynamic adjustment approach which reduces the pixel variation and maintains the image integrity; the prediction method which performs with accuracy; the prediction scheme which helps users generate the stego image satisfying desirable demands. Our schemes expands applications of data hiding for high dynamic range images. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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