A class of adaptive wavelettransforms that map integers to integers based on the adaptive update lifting scheme is presented. The main feature in the adaptive update lifting scheme is that the update lifting step, wh...
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(纸本)0819450804
A class of adaptive wavelettransforms that map integers to integers based on the adaptive update lifting scheme is presented. The main feature in the adaptive update lifting scheme is that the update lifting step, which is considered as an averaging operator and is performed prior to the prediction step, is adapted to the underlying signal content and the adaptivity decisions can be recovered at the synthesis transform without bookkeeping of the adaptivity decisions. The perfect reconstruction criterion for the integer realisation of such transforms are presented in this paper. These adaptive integer-to-integer wavelet transforms can be used in scalable lossless image coding applications. The lossless image coding and spatially scalable decoding performances are demonstrated.
In the secured data communication scenario, image based Reversible Data Hiding (RDH) at transform domain is receiving its due popularity now. In research works so far, evaluation of transforms in RDH is very minor com...
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In the secured data communication scenario, image based Reversible Data Hiding (RDH) at transform domain is receiving its due popularity now. In research works so far, evaluation of transforms in RDH is very minor compared to that of image coding. Since both the areas deal primarily with integers, the present study takes an appreciable step forward by investigating the utilization of integer-to-integer wavelet transforms that have reversibility, which helped in developing high capacity and robust RDH algorithms. The proposed investigation tends to bridge gaps in the area of data hiding with the available coding transforms. In this work, integerwavelettransforms like Haar, 5/3, 2/6, 9/7-M, 2/10, 5/11-C, 5/11A, 6/14, 13/7-T, 13/7-C and 9/7-F are evaluated using a generalized threshold-based histogram shifting technique. This work compares the performance of all integerwavelettransforms and other state of the art techniques with respect to their embedding capacity and image visual quality. This analysis leads to a better understanding of the relationship between the embedding capacity and the stego image quality whenever different wavelets were utilized. (c) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
The use of the discrete wavelet transform (DWT) for embedded lossy image compression is now well established. One of the possible implementations of the DWT is the lifting scheme (LS). Because perfect reconstruction i...
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The use of the discrete wavelet transform (DWT) for embedded lossy image compression is now well established. One of the possible implementations of the DWT is the lifting scheme (LS). Because perfect reconstruction is granted by the structure of the LS, nonlinear transforms can be used, allowing efficient lossless compression as well. The integerwavelet transform (IWT) is one of them. This is an interesting alternative to the DWT because its rate-distortion performances is similar and the differences can be predicted. This topic is investigated in a theoretical framework. A model of the degradations caused by the use of the IWT instead of the DWT for lossy compression is presented. The rounding operations are modeled as additive noises. The noises are then propagated through the LS structure to measure their impact on the reconstructed pixels. This methodology is verified using simulations with random noise as input. It predicts accurately the results obtained using images compressed by the well-known EZW [1] algorithm. Experiments are also performed to measure the difference in terms of bitrate and visual quality. This allows to a better understanding of the impact of the IWT when applied to lossy image compression.
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