Efficient adaptive prediction based reversible image watermarking
01 Sep 2013-Vol. 20, Iss: 12, pp 4540-4544
TL;DR: A new reversible watermarking algorithm based on additive prediction-error expansion which can recover original image after extracting the hidden data is proposed and has a better embedding capacity and also gives better Peak Signal to Noise Ratio (PSNR) as compared to state-of-the-art reversible watermarked schemes.
Abstract: In this paper, we propose a new reversible watermarking algorithm based on additive prediction-error expansion which can recover original image after extracting the hidden data. Embedding capacity of such algorithms depend on the prediction accuracy of the predictor. We observed that the performance of a predictor based on full context prediction is preciser as compared to that of partial context prediction. In view of this observation, we propose an efficient adaptive prediction (EAP) method based on full context, that exploits local characteristics of neighboring pixels much effectively than other prediction methods reported in literature. Experimental results demonstrate that the proposed algorithm has a better embedding capacity and also gives better Peak Signal to Noise Ratio (PSNR) as compared to state-of-the-art reversible watermarking schemes.
Citations
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01 Feb 2016
TL;DR: Experimental results establish that the proposed predictor with optimal embedding outperforms several existing methods on the basis of prediction error estimation.
Abstract: This paper presents a novel prediction error estimation (PEE) based reversible watermarking scheme. A good predictor is key to the performance of this kind of watermarking scheme. A novel gradient based predictor estimates the pixel value based on a 5×5 neighborhood of the pixel. Moreover, the prediction error expansion (PEE) is divided between the current pixel and its top-diagonal neighbor such that distortion remains minimum. Experimental results establish that the proposed predictor with optimal embedding outperforms several existing methods.
3 citations
Cites background from "Efficient adaptive prediction based..."
...Gradient based selective weighting (GBSW)[10] predictor estimates the pixel value based on the context of ten pixels, which claim to outperform predictors like MED and GAP....
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01 Jan 2019
TL;DR: The chapter presents an application of reversible data hiding for the authentication of image travelling over a hostile and insecure communication channel and presents in-depth analysis on the type of predictor and its impact on the capacity of the reversible data hide scheme.
Abstract: The chapter presents an application of reversible data hiding for the authentication of image travelling over a hostile and insecure communication channel. The reversible data resides in the image and tracks any changes done to it on a communication channel. The extraction of data and any modification to its structure reveals changes in the image. This allows the use of data hiding for forensic purpose. The reversible data hiding provides an additional advantage along with active forensics. The image regains original form after removal of the embedded data. However, reversible data hiding is an interplay between the image quality and watermarking capacity. The chapter presents the generic framework for data hiding and discusses its special case reversible data hiding. It presents capacity-behavior analysis of the difference expansion scheme. It performs in-depth analysis on the type of predictor and its impact on the capacity of the reversible data hiding scheme. Finally, the chapter presents a case study to showcase the use of reversible data hiding for image authentication.
2 citations
01 Mar 2017
TL;DR: A hybrid system of reversible Digital Watermarking H-GAWM for medical images offers a significant improvement in terms of imperceptibility for a desired capacity of the mark by comparing with existing approaches.
Abstract: Image watermarking has been generally acknowledged as a pertinent technique for improving authenticity, integrity and data security where medical images are transmitted, stored, retrieved across networks. An improved the quality of remote medical services strictly depends on the ability of the techniques used to ensure ethics and protect the transmitted medical secrets. On the one hand, medical image watermarking must ensure the confidentiality of information. Indeed, private medical data inserted into the image should be imperceptible and can only be retrieved by authorized persons; which prevents any possibility of access, alteration or destruction. On the other hand, several tips must be present in the watermarking scheme in order to implement integrity and to remove any possibility of alteration, using tools that foster the recovery of the initial medical information. Note also that the watermarking scheme used must guarantee the availability of patient data that must be accessible by people adroit at any moment. Finally, we can not forget to mention authentication. Indeed, every information extracted from watermarked image must be identifiable and especially conform with that inserted initially. In this paper, we propose a hybrid system of reversible Digital Watermarking H-GAWM for medical images. The experimental results show that H-GAWM offers a significant improvement in terms of imperceptibility for a desired capacity of the mark by comparing with existing approaches.
2 citations
Cites background or methods from "Efficient adaptive prediction based..."
...We implemented the proposed H-GAWM and compared its performance with companding based RIWA [3] and EAP [24] methods....
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...Consequently, in the subbands LL, the payload bits embedded with the efficient adaptive prediction process EAP is adopted from [24]....
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...V. EXPERIMENTAL RESULTS We implemented the proposed H-GAWM and compared its performance with companding based RIWA [3] and EAP [24] methods....
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...Xuan Approach [23] companding based RIWA [3] EAP [24] H-GAWM...
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...Consequently, in the subbands LL, the payload bits embedded with the efficient adaptive prediction process EAP is adopted from [24]. thus in the other three subbands HH, LH, and HL are divided into miniature blocks, which we will insert them by the compression and expansion process is adopted from [3]....
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01 Nov 2018
TL;DR: For a widespread acceptance of the proposed technique, the embedding and extracting methodologies have been implemented using Field Programmable Gate Array (FPGA), and the imperceptibility, security and bit hiding capacity results are appreciably substantial.
Abstract: Digital information, being discrete in nature, possesses the capability to transfer more information at a faster rate with a significantly higher processing ease, all of which are in sharp contrast to analogue information. This has led to digital information being at the forefront of different types of media like image, video and audio. The only drawback of this has been the rise of copyright infringement issues, whereby the original owner becomes devoid of his claim over his uniquely designed creation because of duplicity and tampering by malicious users. Digital watermarking is a well sought out solution to this. The original user deliberately implants a distinctively identifiable impression onto the digital media for preventing copyright violation. The authors over here have focused on the specific domain of Medical Image Watermarking. Medical images like X-rays, USG, and MRI have revolutionized the medication fraternity by providing enhanced diagnosis and treatment of patients. But at the same time, copyright infringement of the medical images is a growing concern. To curb this problem, a notion of creating a binary masked image in comparison to the original medical image has been suggested. The mask helps in specifically identifying the region of interest (ROI)wherein the encrypted watermark has to be implanted for better imperceptibility and security. The encrypted watermark is embedded in the spatial domain, that is, the Least Significant Bit (LSB)of image pixels are modified in accordance to the watermarking bits. For a widespread acceptance of the proposed technique, the embedding and extracting methodologies have been implemented using Field Programmable Gate Array (FPGA). The imperceptibility, security and bit hiding capacity results are appreciably substantial. Further, a comparison of the suggested technique against some already relevant cutting edge techniques guarantees the superiority of the proposed technique.
2 citations
TL;DR: Experimental results show that proposed scheme achieves better results in terms of EC, PSNR, computational efficiency, image quality, MSE, NCC and SSIM as compared to existing techniques.
Abstract: Reversible image watermarking schemes are used to protect ownership and copyrights of digital images. This paper proposes a novel reversible image watermarking scheme based on adaptive image interpolation, segmentation and additive prediction error expansion (PEE). Proposed interpolation comprises of weighted average of neighboring pixels by allocating higher and lower weights to less and more distant neighboring pixel values respectively. The proposed adaptive image interpolation focuses on detection of edges thus minimizing artifacts imposed by interpolation. The idea of embedding varying amount of watermark bits in different image segments has been explored. Simple linear iterative clustering (SLIC) based image segmentation is performed to separate very sharp, sharp, smooth and very smooth regions in image. Higher number of watermark bits are embedded in sharp regions by using additive prediction error expansion embedding technique. Simulations of proposed and existing techniques were performed on different images and compared using embedding capacity (EC), peak signal to noise ratio (PSNR), computational efficiency, image quality, mean square error (MSE), normalized cross correlation (NCC) and structural similarity index (SSIM). The experimental results show that proposed scheme achieves better results in terms of EC, PSNR, computational efficiency, image quality, MSE, NCC and SSIM as compared to existing techniques.
2 citations
Cites background or methods or result from "Efficient adaptive prediction based..."
...embeds higher amount of watermark bits but also achieves higher PSNR, high image quality index, high SSIM, less MSE, time efficiency and comparable NCC than existing ([8, 9] and [10]) schemes....
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...High grade values of proposed scheme show that majority of the observers found proposed watermarked images closer to original images, than [8, 9] and Kumar et al....
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...The proposed scheme outperforms existing schemes [8, 9] and [10]...
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...[8] CP 24 19 12 7 8 28 3 11 EC (bits) 256727 200999 221109 233306 193284 252639 177688 187731 PSNR (dB) 23....
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...For proposed scheme, the embedding parameters are set with in accordance with existing schemes [8] and [9] for fair analysis....
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References
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TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
Abstract: Reversible data embedding has drawn lots of interest recently Being reversible, the original digital content can be completely restored We present a novel reversible data-embedding method for digital images We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low
2,739 citations
"Efficient adaptive prediction based..." refers methods in this paper
...categories [2]: data compression [3] based RIW, histogram based shifting methods [4]-[6] and difference expansion (DE) [7]-[10] based RIW....
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TL;DR: It is proved analytically and shown experimentally that the peak signal-to-noise ratio of the marked image generated by this method versus the original image is guaranteed to be above 48 dB, which is much higher than that of all reversible data hiding techniques reported in the literature.
Abstract: A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.
2,240 citations
TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.
Abstract: Reversible watermarking enables the embedding of useful information in a host signal without any loss of host information. Tian's difference-expansion technique is a high-capacity, reversible method for data embedding. However, the method suffers from undesirable distortion at low embedding capacities and lack of capacity control due to the need for embedding a location map. We propose a histogram shifting technique as an alternative to embedding the location map. The proposed technique improves the distortion performance at low embedding capacities and mitigates the capacity control problem. We also propose a reversible data-embedding technique called prediction-error expansion. This new technique better exploits the correlation inherent in the neighborhood of a pixel than the difference-expansion scheme. Prediction-error expansion and histogram shifting combine to form an effective method for data embedding. The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion. There is also a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities
1,229 citations
TL;DR: In this paper, a generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve.
Abstract: We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.
1,058 citations
25 May 2003
TL;DR: A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms.
Abstract: This paper presents a novel reversible data hiding algorithm, which can recover the original image without distortion from the marked image after the hidden data have been extracted. This algorithm utilizes the zero or the minimum point of the histogram and slightly modifies the pixel values to embed data. It can embed more data as compared to most of the existing reversible data hiding algorithms. A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms. The algorithm has been applied to a wide range of different images successfully. Some experimental results are presented to demonstrate the validity of the algorithm.
672 citations
"Efficient adaptive prediction based..." refers methods in this paper
...categories [2]: data compression [3] based RIW, histogram based shifting methods [4]-[6] and difference expansion (DE) [7]-[10] based RIW....
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...Ni [4] 5,460 5,421 7,301 16,171 Lin [5] 59,900 19,130 37,644 80,006 Hu [10] 60,241 21,411 28,259 77,254 EAP 66,512 22,685 42,241 91,890...
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