基于多尺度top-hat变换的自适应彩色图像增强

针对传统彩色图像增强过程中的过度增强及空间变化所引起的信息丢失现象,在RGB空间提出一种基于数学形态学top-hat算法,以各分量标准差权重比例为调控因子的彩色图像增强方法。首先,提取R、G、B通道多尺度下的亮、暗细节特征,然后利用控制因子对有应用价值的细节特征进行增强,最后组合三个分量,得到增强的目标图像。实验结果表明,该方法能有效增强图像对比度,避免过度增强,且能很好地保持亮度,视觉效果良好。     

A New Medical Image Enhancement Based on Human Visual Characteristics

Study of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact effectively to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest （ROI） is segmented; then the Un-sharp Masking （USM） is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.     

Investigation of Raman enhancement in hydrothermally roughened SERS-active substrates

In this work, we study surface enhanced Raman spectroscopy (SERS) active substrates for the detection of Rhodamine 6G. To examine the electromagnetic enhancement, we apply the finite-difference time-domain (FDTD) algorithm to analyze the structures by solving a set of coupled Maxwell's equations (Ampere's Law and Faraday's Law) in differential form. The field enhancements are thus investigated in the visible regime with the wavelength of 633 nm. In our experimental measurement, the surface enhanced Raman scattering signals from the surface of substrates with 12-hour treatment and without treatment are performed and compared. Through the three-dimensional (3D) FDTD calculation, we find that the hydrothermally 12-hour treated samples possess significantly vertical variations of surface and thus have relatively larger field enhancement than those without treated. Consequently, it implies a strong positive effect on the surface enhancement which is consistent with the measured intensity.     

基于Gabor滤波器的指纹图像增强算法

介绍了一种基于Gabor滤波器的指纹图像增强算法,该方法对传统的Gabor滤波器的参数和大小进行了优化。实验表明这种算法具有很好的处理效果。     

铸件DR图像工件号的增强和分割

铸件DR(DigitalRadiography,数字化X射线照相)图像中工件号的识别对提高检测信息录入的自动化程度具有重要意义。由于受铸件厚薄不均等因素的影响,某些铸件DR图像字符区域存在字符与背景区分不明显等问题。要正确识别出铸件的工件号,必须对图像进行处理。采用加性模型消除字符与背景区分不明显的影响,gamma校正调整图像灰度范围,可增强对比度,获得适宜于二值化的增强图像。改进基于二次边缘提取的二值化算法,用于对铸件DR字符图像的二值化,可以减少笔画断裂问题,得到良好的二值化字符图像。字符分割采用小波变换提取图像列和的突变信息,从而确定字符间隔,能够完整地分割出每个字符。对实际的铸件DR图像进行实验表明,研究的方法获得了良好的效果,为铸件DR图像的工件号自动识别做好了准备。     

自动图象边缘检测方法的研究

本文提出了一种新的自动图象边缘检测方法,该方法使用新的隶属函数将图象转化为等效的图象模糊特征平面,在此基础上进行模糊增强,然后再转换为空域图象,顾后进行边缘提取,模糊增强提高了低灰度区域和高硬功率和高灰度区域之间的对比度,从而使提取的边缘效果更好,最后本文对具有多峰直方图分布图象的模糊边缘检测问题进行了
了推广。     

自动报靶系统研究综述

介绍了一种基于机器视觉的自动报靶系统,该系统利用CCD摄像机不间断地对靶面进行观测,根据采集的靶面图像的特点和变化,利用计算机图像识别技术检测靶面图像中的真实弹点,然后通过弹点在靶面图中的位置来对弹点区域进行编码。在观测过程中,采用图像灰度配准与增强技术、图像的几何配准技术和小波变换等算法来解决由于光照变化、大风等干扰因素对识别精度的影响。在实际应用中,能够达到较高精度,并能大大减少错报和漏报的情况,该系统精度高、成木低、完全可靠,能够很好地应用于部队训练和射击比赛中有着重要的实际意义和良好的应用前景。     

Simultaneous speckle reduction and contrast enhancement for ultrasound images: Wavelet versus Laplacian pyramid

Speckle can be described as random multiplicative noise. It hampers the perception and extraction of fine details in the image. Speckle reduction techniques are applied to ultrasound images in order to reduce the noise level and improve the visual quality for better diagnoses. It is also used as preliminary treatment before segmentation and classification. Several methods have been proposed for speckle reduction in ultrasound images. Multiscale contrast enhancement has proven to be very efficient for x-ray images. A recent study by Dippel et al. doing a comparison, contrast enhancement of radiographs (x-ray and mammography), between the Laplacian pyramid and the wavelet one proves that the Laplacian pyramid method gives a better result than the wavelet one; the filtering aspect was not taken into account. In ultrasound images a strong contrast variation exists which is different from x-ray and mammography. In this paper a wavelet pyramid with simultaneous speckle reduction and contrast enhancement was applied for the first time on ultrasound images with the area of interest and compared to a Laplacian enhancement pyramid. The optimum choice of wavelet bases for ultrasound images is investigated in this study. In order to realize a fair comparison, the same nonlinear modification in both multiscale schemes is used. The comparison proves that the wavelet pyramid gives a much better result than the Laplacian one for simultaneous speckle reduction and contrast enhancement of ultrasound images. The text was submitted by the author in English. Ali Samir Saad, 1964. 1996 PhD in image processing, Polytechnics School of the Engineering University of Nantes, France. 1993 Masters in Electronics. 1990 Masters in Digital Image Processing, Institute of Computer Sciences and Communication University of Rennes, France. 1989 BS in Electrical Engineering, University of Saint-Etienne. Academy of Lyon, France. 1996–2000 Research associate at the National Center for Macromolecular Imaging. Baylor, Houston, Texas. Assistant professor at King Saud University, Dept. of Biomedical Technology. Area of research in medical image processing and analysis, 23 publications, member of the American Association for the Advancement of Sciences. Marquis Who’s Who in the World; Cambridge Blue Book 2006.     

Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.

神经网络自适应噪声对消的研究

基于神经网络中自适应线性单元(ADALINE),结合传统自适应噪声对消原理,提出了一种基于ADALINE的改进型自适应噪声对消器。经仿真和实例证明,具有很强的噪声滤除能力和鲁棒性。