Integral imaging-based cryptographic algorithms provide a new way to design secure and robust image encryption systems. In this paper, we introduce a performance-enhanced image encryption scheme based on depth-convers...
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Integral imaging-based cryptographic algorithms provide a new way to design secure and robust image encryption systems. In this paper, we introduce a performance-enhanced image encryption scheme based on depth-conversion integral imaging and hybrid cellular automata (CA), aiming to meet the requirements of secure image transmission. First, the input image is decomposed into an elemental image array (EIA) using the depth converted integral imaging technique. The obtained elemental images then are encrypted by utilizing the CA model and chaotic sequence. The conventional computational integral imaging reconstruction (CIIR) technique is a pixel-superposition technique. The resolution of the reconstructed image is dramatically degraded by the large magnification factor in the superposition process as the pickup distance increases. In the proposed reconstruction process, the pixel mapping technique is introduced to solve these problems. A novel property of the proposed scheme is its depth-conversion property, which reconstructs an elemental image originally recorded at long distances from the pinhole array as one that was recorded near the pinhole array and consequently reduces the magnification factor. The results of numerical simulations demonstrate the effectiveness and security of the proposed scheme. (C) 2015 Elsevier B.v. All rights reserved.
This paper presents a complexity control system for depth maps intra-frame prediction of the 3D-High Efficiency video Coding (3D-HEvC) standard. The proposed system uses a Proportional-Integral-Derivative controller o...
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This paper presents a complexity control system for depth maps intra-frame prediction of the 3D-High Efficiency video Coding (3D-HEvC) standard. The proposed system uses a Proportional-Integral-Derivative controller over the Simplified Edge Detector heuristic to skip the Depth Modeling Modes (DMMs) evaluation dynamically according to a defined target rate. When analyzing the proposed system under Common Test Conditions, the proposed controller stabilizes the system to the target rate (i.e., the percentage of DMMs evaluation) after encoding a few frames, with negligible encoding efficiency impacts. The BD-rate degradation varies from 0.50% to 0.20%, on average, when the target rates vary from 5% to 15%. These target rates imply in an aggressive reduction in the DMMs evaluations, skipping the DMMs from 85% to 95% of the cases.
Most current high contrast imaging point spread function (PSF) subtraction algorithms use some form of a least-squares noise minimization to find exoplanets that are, before post-processing, often hidden below the ins...
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ISBN:
(纸本)9781510601987
Most current high contrast imaging point spread function (PSF) subtraction algorithms use some form of a least-squares noise minimization to find exoplanets that are, before post-processing, often hidden below the instrumental speckle noise. In the current standard PSF subtraction algorithms, a set of reference images is derived from the target image sequence to subtract each target image, using Angular and/or Simultaneous Spectral Differential Imaging (ADI, SSDI, respectively). However, to avoid excessive exoplanet self-subtraction, ADI and SSDI (in the absence of a strong spectral feature) severely limit the available number of reference images at small separations. This limits the performance of the least-squares algorithm, resulting in lower sensitivity to exoplanets at small angular separations. Possible solutions are to use additional reference images by acquiring longer sequences, use SSDI if the exoplanet is expected to show strong spectral features, or use images acquired on other targets. The latter option, known as Reference Star Differential Imaging (RSDI), which relies on the use of reference images that are highly correlated to the target image, has been ineffective in previous ground-based high contrast imaging surveys. The now >200 target reference library from the Gemini Planet imager Exoplanet Survey (GPIES) allows for a detailed RSDI analysis to possibly improve contrast performance near the focal plane mask, at similar to 2-7 lambda/D separations. We present the results of work to optimize PSF subtraction with the GPIES reference library using a least-squares algorithm designed to minimize speckle noise and maximize planet throughput, thus maximizing the planet signal to noise ratio (SNR). Using December 2014 51 Eri GPI data in the inner 100 mas to 300 mas annulus, we find no apparent improvement in SNR when using RSDI and/or our optimization scheme. This result, while still being investigated, seems to show that current algorithms on ADI+SSDI da
Feature of modern infocommunication systems is expeditious exchange of information that makes a problem of ensuring quality and reliability of the obtained information actual. For elimination or minimization of the de...
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ISBN:
(纸本)9781509040490
Feature of modern infocommunication systems is expeditious exchange of information that makes a problem of ensuring quality and reliability of the obtained information actual. For elimination or minimization of the destabilizing impact of noise and hindrances in such systemsvarious methods and algorithms of preliminary information processing are widely used, in particular, procedures of digital filtration of signals and images. Procedure of creation of the nonlinear SvD filter with adaptation to local properties of an observed signal is stated. Comparative examples of filtration of hindrances in a problem of processing of images are given, efficiency of the offered method is shown. The lines of further researches are defined.
The article describes parallel implementations of two parametric identification algorithms. The first algorithm is based on the estimation of Bravais unit cell parameters, and the second one estimates Wigner-Seitz cel...
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The article describes parallel implementations of two parametric identification algorithms. The first algorithm is based on the estimation of Bravais unit cell parameters, and the second one estimates Wigner-Seitz cell volumes. The developed parallel implementations are based on the two-tier model of concurrency. An external tier of concurrency uses Message Passing Interface (MPI) technique to distribute parametric identification tasks between computing nodes. An internal tier uses Open Multi-processing (OpenMP) technique to split single steps of the parametric identification algorithms into independent subtasks. Experimental results on multi-processor/multi-core systems have demonstrated almost linear speedup of the parallel implementations, confirmed the effectiveness of the two-tier concurrency model and proved the stability of the identification approach under lattice distortion.
In this paper, we describe a modification of the previously developed on-board imageprocessing method applied to hyperspectral images. algorithms on which the method is based were finalized and parametrically adjuste...
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In this paper, we describe a modification of the previously developed on-board imageprocessing method applied to hyperspectral images. algorithms on which the method is based were finalized and parametrically adjusted. Computational experiments consider formation and storage specifics for hyperspectral images. It has been shown that the proposed method based on HGI-compression can be recommended for implementation in on-board processingsystems and transmission over communication channels.
Quantitative acoustic microscopy (QAM) is an imaging modality which uses very-high-frequency ultrasound (i.e., >200 MHz) to form two-dimensional (2D) quantitative images of acoustical and mechanical properties of s...
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ISBN:
(纸本)9781509041183
Quantitative acoustic microscopy (QAM) is an imaging modality which uses very-high-frequency ultrasound (i.e., >200 MHz) to form two-dimensional (2D) quantitative images of acoustical and mechanical properties of soft tissues with microscopic resolution (i.e., better than 8 μm). The key component of a QAM system is the ultrasound transducer which must be broadband, have a very small F-number (i.e., <;1.2), and good sensitivity. In this study, two QAM systems based on a 250-MHz and a 500-MHz transducer are presented, yielding 2D quantitative images at spatial resolution of 7 μm and 4 μm respectively. Thin tissue sections obtained using a microtome or cryotome are raster scanned with precise motors and pulse-echo RF signals are digitized. Inverse models are then used to process each RF signal individually to estimate acoustic impedance, speed of sound, and acoustic attenuation as well as derived parameters such as bulk modulus, mass density, and compressibility. To illustrate the QAM technology and signal processingalgorithms, images from cancerous human lymph nodes and ophthalmologic samples are presented and coregistered with histology photomicrographs.
In order to accelerate the acquisition process in multiple-coil Magnetic Resonance scanners, parallel techniques were developed. These techniques reduce the acquisition time via a sub-sampling of the k-space and a rec...
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In order to accelerate the acquisition process in multiple-coil Magnetic Resonance scanners, parallel techniques were developed. These techniques reduce the acquisition time via a sub-sampling of the k-space and a reconstruction process. From a signal and noise perspective, the use of a acceleration techniques modify the structure of the noise within the image. In the most common algorithms, like SENSE, the final magnitude image after the reconstruction is known to follow a Rician distribution for each pixel, just like single coil systems. However, the noise is spatially non-stationary, i.e. the variance of noise becomes x-dependent. This effect can also be found in magnitude images due to other processing inside the scanner. In this work we propose a method to adapt well-known noise filtering techniques initially designed to deal with stationary noise to the case of spatially variant Rician noise. The method copes with inaccurate estimates of variant noise patterns in the image, showing its robustness in realistic cases. The method employs a consensus strategy in conjunction with a set of aggregation functions and a penalty function. Multiple possible outputs are generated for each pixel assuming different unknown input parameters. The consensus approach merges them into a unique filtered image. As a filtering technique, we have selected the Linear Minimum Mean Square Error (LMMSE) estimator for Rician data, which has been used to test our methodology due to its simplicity and robustness. Results with synthetic and in vivo data confirm the good behavior of our approach. (C) 2016 Elsevier B.v. All rights reserved.
Joint geometry measurement is a key task for welding automation. Among the sensors used for this purpose, the Laser Triangulation Sensors for welding (LTS) are the ones that best characterize the joint geometry. Root ...
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Joint geometry measurement is a key task for welding automation. Among the sensors used for this purpose, the Laser Triangulation Sensors for welding (LTS) are the ones that best characterize the joint geometry. Root gap measurement is especially important for success in the automated root pass deposition, with production and quality benefits in different applications, such as pipeline construction for the Oil & Gas industry. The measurement of this feature is sensitive to noises generated by welding and joint surface reflexivity. The imageprocessingalgorithms for gap measurement available in literature do not have the desired characteristics of measurement error and flexibility for dimensional variability of welding joints. This paper presents a new algorithm for root gap measurement of "v" type joints using a linear adjustment technique. This developed algorithm was evaluated from measurement errors found in images captured before and during orbital welding procedure of a standard test piece. The same images were processed with pattern correlation algorithm and derivative algorithm, both presented in academic papers. The proposed algorithm presented the best results of measurement error, robustness and flexibility.
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