Intelligent reversible watermarking technique in medical images using GA and PSO

The advances in recording, editing, and broadcasting multimedia contents in digital form motivate to protect these digital contents from illegal use, such as duplication, manipulation, and redistribution. However, watermarking algorithms are designed to satisfy requirements of applications, as different applications have different concerns. We intend to design a watermarking algorithm for applications which require high embedding capacity and imperceptibility, to maintain the integrity of the host signal as well as embedded information. Reversible watermarking is a promising technique which satisfies our requirements. In this paper, we concentrate on improving the watermark capacity and reducing the perceptual degradation of an image. We investigated the Luo's [1] additive interpolation-error expansion algorithm and enhanced it by incorporating with two intelligent techniques: genetic algorithm (GA), and particle swarm optimization (PSO). Genetic algorithm is applied to exploit the correlation of image pixel values to obtain better estimation of neighboring pixel values, which results in optimal balance between information storage capacity and imperceptibility. Particle swarm optimization (intelligent technique) is also applied for the same purpose. Experimental results show that PSO and GA nearly give the same results, but GA outperforms the PSO. Experimental results also reveal that the proposed strategy outperforms the state of art works in terms of perceptual quality and watermarking payload.     

Multi parameter optimization of Raman Fiber Amplifier using genetic algorithm for S band dense wavelength division multiplexed system

A simple genetic algorithm is implemented to perform multi parameter optimization of Raman Fiber Amplifier for 100 channel S band dense wavelength division multiplexed system at 25 GHz interval. A cost effective system using single Raman pump is investigated aiming at maximum average gain. The single counter propagating pump is optimized to frequency of 211.528 THz and 652.93 mW power level with optimum Raman fiber length of 44.064 Km. There is evidence to show that the optimum solution presents a small gain variation (less than 3 dB) over an effective bandwidth covering 197–199.475 THz. The optimized configuration enabled an adequate system performance in terms of acceptable Q-factor (19.52 dB) and BER (1.46 × 10⁻²¹).     

Synthesis of resonant cavities having continuum spectra by genetic algorithm

This paper proposes a novel method for generating continuum spectra with possible applications in WDM access networks. This new method would allow the development of a simple continuum laser structure with better performances in terms of cost and simplicity than those of present supercontinuum sources. In this aim, we will analyze the possibility to broaden the resonant modes of a Fabry–Perot cavity by operating only on the design of one of the cavity's Bragg mirrors. Firstly we considered the conditions which a Bragg grating must satisfy in order to broaden the resonant modes of a resonant cavity. Because an exact solution is not physical possible, the genetic algorithm is the best available tool for the design of such a grating. An active medium is then added inside the cavity and its behavior below threshold is simulated. The spectra thus simulated are continuum over 5–15 nm.     

三维相位展开算法在精密运动测试中的应用

三维相位展开算法将基于空间的相位展开算法拓展到时间轴上,包含了一维时间和二维空间信息,适合于运动测试。通过建立一维时间相位展开算法的数学模型,分析了该算法运动测试的基本原理,讨论了在精密测试中的使用方法和适用范围,并对微谐振器的微结构进行运动测试。实验表明,算法在相位展开中引入时间信息,不仅消除了形变测量中需选取静止点为相位参考点或参考平面的限制,还可以同时测量物体表面某点纳米级的离面运动曲线和表面形变。     

货车枕簧丢失故障动态图像识别方法

针对货车运行故障动态图像检测,提出无故障目标识别工作模式,解决货车枕簧丢失故障的自动识别问题。利用Haar特征提取枕簧特征信息,基于AdaBoost算法选取特征并构建层叠分类器,等比缩放搜索窗口检测货车图像,最终分选出无故障的枕簧图像,从而大大地减少了待识别图像的数量,显著地提高了人工识别效率。实验表明,该算法使用的特征简单,搜索策略高效,不受枕簧位置、缩放和旋转的影响,抗噪能力强,对分辨率低、局部遮挡、光照不足或过度曝光等质量较差的图像仍具有很强的适应性,所提出的方案能够满足全天候条件下的货车枕簧目标识别,为货车故障动态图像检测的工程化应用奠定了基础。     

Image watermarking by using phase retrieval algorithm in gyrator transform domain

We propose an image watermarking scheme based on the phase retrieval algorithm in gyrator domain. The watermark is converted into a noise-like image by Arnold transform. The scrambled image is regarded as the amplitude of gyrator spectrum. The Gerchberg-Saxton algorithm is employed to obtain the unknown phase function in gyrator pair, in which the host image is the amplitude of input function. The phase information and the parameters of the two transforms serve as the key of watermarking algorithm. The numerical simulation has demonstrated the performance of the proposed algorithm.     

太阳米粒结构相关哈特曼-夏克波前传感模拟研究

基于互相关因子和绝对差分算法以及相关哈特曼－夏克波前传感器的基本原理，根据室内模拟太阳米料结构研究了低对比度扩展目标情况下应用相关哈特曼－夏克波前传感器探测波前误差的可行性，结果表明，相关哈特曼－夏克波前传感器能够有效探测光学波前误差。     

改进的盲解卷积技术在远距离激光光斑图像复原中的应用

为了提高外场实验中远距离测量激光光斑位置的精度,提出利用盲解卷积技术对光斑图像进行事后复原来削弱大气湍流对光斑成像的影响。首先,介绍了经典盲解卷积算法,分析了其不足之处,并提出了一种改进的盲解卷积算法。为了提高目标函数的收敛性和收敛速度,在TV(Total Variation)目标函数加入惩罚项,并对交替迭代法进行改进。然后,用数学方法证明了改进的盲解卷积算法的收敛性。最后,进行了仿真实验。与传统算法相比,用改进算法恢复的图像信噪比至少提升了15%。文中给出了外场试验图像的实际复原效果。     

A survey on HHL algorithm: From theory to application in quantum machine learning

The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum linear system of equations that may be found at the core of various scientific applications and quantum machine learning models including the linear regression, support vector machines and recommender systems etc. After reviewing the necessary background on elementary quantum algorithms, we provide detailed account of how HHL is exploited in different quantum machine learning (QML) models, and how it provides the desired quantum speedup in all these models. At the end, we briefly discuss some of the remaining challenges ahead for HHL-based QML models and related methods.