Most proposed digital watermarking algorithms are sensitive to geometric attacksbecause the synchronization information of watermark embedding and detection is destroyed. Inthis letter a novel synchronization recovery...Most proposed digital watermarking algorithms are sensitive to geometric attacksbecause the synchronization information of watermark embedding and detection is destroyed. Inthis letter a novel synchronization recovery scheme based on image normalization is proposed. Thepresented scheme does not require the original image and can be applied to various watermarksystems. A wavelet-based watermarking scheme is proposed as an example and experimentalresults show that it is robust to geometric attacks.展开更多
The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal ...The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.展开更多
In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted...In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted. Furthermore, the locally most stable feature points are used to generate several nonoverlapped circular regions. These regions are then rotation normalized to generate the invariant regions. Watermark embedding and extraction are implemented in the invariant regions in discrete cosine transform domain. In the decoder, the watermark can be extracted without the original image. Simulation results show that the proposed scheme is robust to traditional signal processing attacks, RST attacks, as well as some combined attacks.展开更多
Geometric distortions are simple and effective at- tacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchro...Geometric distortions are simple and effective at- tacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchroniza- tion between the watermark reader and the embedded water- mark. In this paper, we propose a blind content-based image watermarking scheme against geometric distortions. Firstly, the MSER detector is adopted to extract a set of maximally stable extremal regions which are affine covariant and robust to geometric distortions and common signal processing. Sec- ondly, every original MSER is fitted into an elliptical region that was proved to be affine invariant. In order to achieve rota- tion invariance, an image normalization process is performed to transform the elliptical regions into circular ones. Finally, watermarks are repeatedly embedded into every circular disk by modifying the wavelet transform coefficients. Experimen- tal results on standard benchmark demonstrate that the pro- posed scheme is robust to geometric distortions as well as common signal processing.展开更多
Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. In this paper, we propose...Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. In this paper, we propose a geometrically invariant digital watermarking method for color images. In order to synchronize the location for watermark insertion and detection, we use a multi-scale Harris-Laplace detector, by which feature points of a color image can be extracted that are invariant to geometric distortions. Then, the self-adaptive local image region （LIR） detection based on the feature scale theory was considered for watermarking. At each local image region, the watermark is embedded after image normalization. By binding digital watermark with invariant image regions, resilience against geometric distortion can be readily obtained. Our method belongs to the category of blind watermarking techniques, because we do not need the original image during detection. Experimental results show that the proposed color image watermarking is not only invisible and robust against common signal processing such as sharpening, noise adding, and JPEG compression, but also robust against the geometric distortions such as rotation, translation, scaling, row or column removal, shearing, and local random bend.展开更多
Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy.Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for...Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy.Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments.Here,we present an automated method of correcting first-and second-order aberrations called BEACON,which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings.We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano-and atomic-scale experiments.BEACON can correct all firstand second-order aberrations simultaneously to achieve an initial alignment and first-and secondorder aberrations independently for fine alignment.Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.展开更多
基金the National Natural Science Foundation of China (No.60172065)
文摘Most proposed digital watermarking algorithms are sensitive to geometric attacksbecause the synchronization information of watermark embedding and detection is destroyed. Inthis letter a novel synchronization recovery scheme based on image normalization is proposed. Thepresented scheme does not require the original image and can be applied to various watermarksystems. A wavelet-based watermarking scheme is proposed as an example and experimentalresults show that it is robust to geometric attacks.
基金This work is supported by the National Natural Science Foundation of China(No.41604039,41604102,41764005,41574078)Guangxi Natural Science Foundation project(No.2020GXNSFAA159121,2016GXNSFBA380215).
文摘The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.
基金the Hi-Tech Research and Development Program of China (2006AA01Z127)National Natural Science Foundation of China (60572152 and 60603011)Ph. D. Programs Foundation of Ministry of Education of China (20060701004)
文摘In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted. Furthermore, the locally most stable feature points are used to generate several nonoverlapped circular regions. These regions are then rotation normalized to generate the invariant regions. Watermark embedding and extraction are implemented in the invariant regions in discrete cosine transform domain. In the decoder, the watermark can be extracted without the original image. Simulation results show that the proposed scheme is robust to traditional signal processing attacks, RST attacks, as well as some combined attacks.
文摘Geometric distortions are simple and effective at- tacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchroniza- tion between the watermark reader and the embedded water- mark. In this paper, we propose a blind content-based image watermarking scheme against geometric distortions. Firstly, the MSER detector is adopted to extract a set of maximally stable extremal regions which are affine covariant and robust to geometric distortions and common signal processing. Sec- ondly, every original MSER is fitted into an elliptical region that was proved to be affine invariant. In order to achieve rota- tion invariance, an image normalization process is performed to transform the elliptical regions into circular ones. Finally, watermarks are repeatedly embedded into every circular disk by modifying the wavelet transform coefficients. Experimen- tal results on standard benchmark demonstrate that the pro- posed scheme is robust to geometric distortions as well as common signal processing.
基金the National Natural Science Foundation of China (Grant Nos. 60773031, 60873222)the Open Foundation of State Key Laboratory of Networking and Switching Technology of China (Grant No. SKLNST-2008-1-01)+2 种基金the Open Foundation of State Key Laboratory of Information Security of China (Grant No. 03-06)the Open Foundation of State Key Laboratory for Novel Software Technology of China (Grant No. A200702)Liaoning Research Project for Institutions of Higher Education of China (Grant No. 2008351)
文摘Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. In this paper, we propose a geometrically invariant digital watermarking method for color images. In order to synchronize the location for watermark insertion and detection, we use a multi-scale Harris-Laplace detector, by which feature points of a color image can be extracted that are invariant to geometric distortions. Then, the self-adaptive local image region （LIR） detection based on the feature scale theory was considered for watermarking. At each local image region, the watermark is embedded after image normalization. By binding digital watermark with invariant image regions, resilience against geometric distortion can be readily obtained. Our method belongs to the category of blind watermarking techniques, because we do not need the original image during detection. Experimental results show that the proposed color image watermarking is not only invisible and robust against common signal processing such as sharpening, noise adding, and JPEG compression, but also robust against the geometric distortions such as rotation, translation, scaling, row or column removal, shearing, and local random bend.
基金funded by the US Department of Energy in the program "Electron Distillery 2.0: Massive Electron Microscopy Data to Useful Information with AI/ML."Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231+1 种基金This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award BES-ERCAP0028035S.M.R. and C.O. acknowledge support from the U.S. Department of Energy Early Career Research Award program. J.P. acknowledges financial support from the National Research Foundation of Korea (NRF) grant, funded by the Korea government (MSIT) (Grant No. RS-2023-00283902, and RS-202400408823). We gratefully acknowledge CEOS, GmbH for providing the server enabling communication with the corrector and I. Massmann for technical assistance.
文摘Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy.Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments.Here,we present an automated method of correcting first-and second-order aberrations called BEACON,which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings.We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano-and atomic-scale experiments.BEACON can correct all firstand second-order aberrations simultaneously to achieve an initial alignment and first-and secondorder aberrations independently for fine alignment.Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.
