An adaptive color image watermarking using RDWT-SVD and artificial bee colony based quality metric strength factor optimization

Double-encrypted watermarking algorithm based on cosine transform and fractional Fourier transform in invariant wavelet domain

A view-free image stitching network based on global homography

This paper proposes a blind and robust color image watermarking method based on a new three-dimensional Henon chaotic map and uses integer wavelet transform, discrete wavelet transform and contourlet transform in embedding and extracting processes. In the presented approach, color images are divided into $$4\times 4$$ main nonoverlapping parts, and one of the transforms is applied to these parts. Then the low–low sub-band of transform is selected. The suggested map is used to find $$2\times 2$$ blocks in the embedding process. The bits of watermark are embedded in the parts of images to increase the robustness of the proposed watermarking scheme. To improve the quality of the final watermark, the suggested technique uses a correction process in the extracting process. In this paper, the bifurcation diagram, Lyapunov exponent, cobweb plot and trajectory diagram are used to show the chaotic behavior of the proposed map. Based on DIEHARD, ENT and NIST test suites, the suggested map can be used as a pseudo-random number generator. The simulation results show that the proposed watermarking algorithm is robust against most image processing attacks like salt & pepper, cropping, low-pass filter, wiener filter, blurring, etc. The comparison results between the suggested watermarking scheme, and some similar methods show that the presented technique has good performance, imperceptibility, acceptable robustness and outperforms most related methods.

A blind and robust color images watermarking method based on block transform and secured by modified 3-dimensional Hénon map

In this article, we propose a novel approach to accelerate the processing of 3D images by the discrete orthogonal moments of Charlier. The proposed approach is based on two fundamental notions: The first is the acceleration of the computing time of Charlier discrete orthogonal polynomials and moments in the case of the 3D image using digital filters. The second is the description of the 3D image by a set of cuboids of fixed size instead of individual voxels by decomposing the image by cuboids of small sizes to ensure numerical stability. By applying this method, the 3D Charlier moments are calculated from the cuboids instead of the whole image, as the image processing will be locally in each cuboid. This method allows us to speed up the computation time of the moments and to avoid the problem of propagation of digital errors encountered as well when using of digital filters for 3D images of large sizes. The simulation results show the effectiveness of the proposed method in terms of the computation time of the 3D moments of Charlier and in terms of quality of 3D image.

Fast 3D image reconstruction by cuboids and 3D Charlier’s moments

Digital watermarking is one of the most effective methods for protecting multimedia from different kind of threats. It has been used for many purposes, like copyright protection, ownership identification, tamper detection, etc. Many watermarking applications require embedding techniques that provide robustness against common watermarking attacks, like compression, noise, filtering, etc. In this paper, an optimized robust watermarking method is proposed using Fractional Fourier Transform and Singular Value Decomposition. The approach provides a secure way for watermarking through the embedding parameters that are required for the watermark extraction. It is a block-based method, where each watermark bit is embedded in its corresponding image block. First, the transform is applied to each block, and then the singular values are evaluated through which the embedding modification is performed. The optimum fractional powers, of the transform, and the embedding strength factor are evaluated through a Meta-heuristic optimization to optimize the watermark imperceptibility and robustness. The Artificial Bee Colony is used as the Meta-heuristic optimization method. A fitness function is employed, at the optimization process, through which the maximum achievable robustness can be provided without degrading the watermarking quality below a predetermined quality threshold Qth. The effectiveness of the proposed method is demonstrated through a comparison with recent watermarking techniques in terms of the watermarking performance. The watermarking quality and robustness are evaluated for different quality threshold values. Experimental results show that the proposed approach achieves a better quality compared to that of other existing watermarking methods. On the other hand, the robustness is examined against the most common applied attacks. It is noticed that the proposed method can achieve a higher robustness degree when decreasing the quality threshold value.

Optimized SVD-based robust watermarking in the fractional Fourier domain

Legendre moments and their invariants for 2D and 3D image/objects are widely used in image processing, computer vision, and pattern recognition applications. Reconstruction of digital images by nature required higher-order moments to get high-quality reconstructed images. Different applications such as classification of bacterial contamination images utilize high-order moments for feature extraction phase. For big size images and 3D objects, Legendre moments computation is very time-consuming and compute-intensive. This problem limits the use of Legendre moments and makes them impractical for real-time applications. Multi-core CPUs and GPUs are powerful processing parallel architectures. In this paper, new parallel algorithms are proposed to speed up the process of exact Legendre moments computation for 2D and 3D image/objects. These algorithms utilize multi-core CPUs and GPUs parallel architectures where each pixel/voxel of the input digital image/object can be handled independently. A detailed profile analysis is presented where the weight of each part of the entire computational process is evaluated. In addition, we contributed to the parallel 2D/3D Legendre moments by: (1) a modification of the traditional exact Legendre moment algorithm to better fit the parallel architectures, (2) we present the first parallel CPU implementation of Legendre moment, and (3) we present the first parallel CPU and GPU acceleration of the reconstruction phase of the Legendre moments. A set of numerical experiments with different gray-level images are performed. The obtained results clearly show a very close to optimal parallel gain. The extreme reduction in execution times, especially for 8-core CPUs and GPUs, makes the parallel exact 2D/3D Legendre moments suitable for real-time applications.

Fast computation of 2D and 3D Legendre moments using multi-core CPUs and GPU parallel architectures

Fast parallel beam propagation method based on multi-core and many-core architectures

Two Pulse Shape Discrimination (PSD) techniques are proposed based on Cross Correlation (CC) and Principal Component Analysis (PCA). In CC-based PSD, two schemes are proposed to discriminate between different decay scintillation pulses. The first CC-based scheme is applied to digitized scintillation pulses in time-domain with different numbers of samples ranging from the last two samples up to the full length. The second CC-based scheme is applied to frequency components of the scintillation pulses, where pulses are transformed using one of the following transforms; Discrete Sine Transform (DST), Discrete Cosine Transforms (DCT), Discrete Wavelet Transforms (DWT), and Fast Fourier Transform (FFT). On the other hand, in PCA-based PSD technique, two schemes are applied to the digitized pulses in time domain and the transformed pulses coefficients in the frequency domain, respectively, as in the previous sequence.

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Pulse Shape Discrimination Techniques based on Cross-correlation and Principal Component Analysis

absorption of radiation in multicrystal PET detectors results in different decay-time pulses. The differences between these pulse decay time constants are used to discriminate between different scintillator materials. In this paper, pulse shape discrimination (PSD) techniques based on the discrete sine transform (DST) and discrete cosine transform (DCT) are proposed. These transformations are used to extract frequency- domain features for discrimination. Comparison of the proposed PSD techniques was performed on digitized pulses from the LSO/LuYAP phoswich detector. The comparison between different DST- and DCT-types turned out that DST-type 3 gives the best PSD efficiency of 98.79%, while DCT-type 2 gives 98.12%.

/pdf/dst-and-dct-based-depth-of-interaction-doi-determining-4ydi7hria2.pdf

M. Sayed

Papers

Optimized SVD-based robust watermarking in the fractional Fourier domain

Fast computation of 2D and 3D Legendre moments using multi-core CPUs and GPU parallel architectures

Fast parallel beam propagation method based on multi-core and many-core architectures

Pulse Shape Discrimination Techniques based on Cross-correlation and Principal Component Analysis

DST and DCT-based Depth of Interaction (DOI) Determining Techniques for LSO and LuYAP Scintillation Detectors in PET