新IFS分形图象盒维数的EMMS位模拟计算

针对新获取的IFS分形图像进一步分析的需要,提出位模拟分维计算,极大地改进了原有盒维数计算的诸多不便,在普通PC机上一次性的计算即可满足一般性要求,或提供进一步处理的精质数据。完成了完整的实用软件,并采用该算法具体计算了墨竹叶分形集和扩散集及另外几种标准IFS集合的盒维数     

新IFS分形图象盒维数的EMMS位模拟计算

针对新获取的IFS分形图像进一步分析的需要，提出位模拟分维计算，极大地改进了原有盒维数计算的诸多不便，在普通PC机上一次性的计算即可满足一般性要求，或提供进一步处理的精质数据。完成了完整的实用软件，并采用该算法具体计算了墨竹叶分形集和扩散集及另外几种标准IFS集合的盒维数。     

基于分形脊波神经网络的遥感图像分类研究

在分形理论和脊波神经网络的基础上，综合利用彩色遥感图像的光谱、纹理和形状特征，提出了一种彩色遥感图像的分类新方法．该方法把彩色图像的蓝、绿、红波段作为3个光谱特征，由分形理论计算的DBC维和多重分形维数作为2个纹理特征，平均不变矩作为1个形状特征，并利用对曲线具有极强方向识别能力的脊波神经网络作为分类器．实验结果表明，提出的彩色遥感图像分类方法具有较高的分类准确率和较强的抗噪音能力．     

基于改进中值滤波和提升小波变换的阈值去噪方法研究

对于实际拍摄的一些图像信噪比低,噪声密度大,且含有混合噪声,而现有算法大多只能去除单一噪声的问题。针对混合噪声中含有的脉冲噪声和高斯噪声,提出基于改进中值滤波和提升小波变换去噪相结合的方法。去噪过程中,使用中值滤波器提取脉冲噪声并采用中值滤波算法滤波后,构造提升小波,采用改进阈值函数提升小波阈值去噪方法去除高斯噪声。实验结果表明,当噪声值(ρ,σ)=(0.4, 20)时,采用本文去噪方法,峰值信噪比(PSNR)为34.002 1,平均绝对误差(MAE)为2.365 3。     

基于非局部均值和SUSAN算子的混合噪声滤除

为了更好地滤除图像中脉冲噪声和高斯噪声组成的混合噪声,提出了一种基于非局部均值和Small Univalue Segment Assimilating Nucleus(SUSAN)算子的混合噪声滤除方法.该方法首先根据脉冲噪声点与角点之间吸收核同值区形状特征的不同,采用SUSAN算子检测出大量的特征点,特征点主要是脉冲噪声点,也可能含有小部分角点.将特征点进行排序,出现频次最高两位的点为脉冲噪声点.然后采用改进的均值滤波法计算脉冲噪声点邻域中非脉冲噪声点的均值,以此替换脉冲噪声点灰度值.最后针对已滤除脉冲噪声的图像,采用考虑了图像块信息的非局部均值方法滤除剩余的高斯噪声.去噪实验结果表明:与自适应中值和加权均值结合的方法、中值滤波与小波结合的方法、脉冲耦合神经网络与中值滤波结合的方法相比,本文方法主观视觉效果更好,能够更好地保留图像中的边缘细节,客观评价指标峰值信噪比有较大的提高,滤除混合噪声的优势明显.     

基于FRFT域分形特征的压制干扰存在性检测（英文）

基于分数阶傅里叶变换(FRFT)域的分形特征研究压制干扰的存在性检测问题。首先,分析了典型的三种压制干扰的分形特征,说明了典型压制干扰信号具有分形特性,并采用盒维数和信息维数定量描述它们的分形特征。然后,发现了压制干扰和高斯白噪声在FRFT域具有不同的分形特征,进而提出了一种检测压制干扰存在性的方法。最后,仿真验证了该方法的有效性和优越性。     

分形维数海豚哨声信号检测方法

针对海豚哨声信号自动检测的问题,提出一种基于分形维数的自适应阈值海豚哨声信号检测方法。对待检测声信号计算盒分形维数,根据得到的盒分形维数特征值,通过模糊C均值聚类自适应确定检测阈值,实现海豚哨声信号的自动检测。文中对水池录制的海豚声信号进行了数据分析,利用哨声信号盒分形维数对哨声信号段与非信号段进行检测,并与基于谱熵的方法进行对比,获得了较高的检测率以及较低的虚警率,可以适用于海豚哨声信号的自动检测与分割。     

二维电磁逆散射问题的时域高斯-牛顿反演算法

为了直接利用超宽带(UWB)时域测量数据,同时重建二维(2D)目标(OI)的介电常数和电导率,本文将频域高斯-牛顿反演(GNI)算法发展为时域形式.迭代重建过程中,正问题由时域有限差分(FDTD)法求解,而逆问题的病态特性用自适应正则化技术抑制.四类数值算例中,噪声影响均被考虑,仿真结果初步证实了改进算法的可行性和鲁棒性.重建图像呈现超分辨率(SR),有望应用到早期乳腺癌检测等实际问题中.     

基于中值滤波和提升小波分析的图像去噪方法研究

 针对现有算法大多对单一高斯噪声或脉冲噪声进行图像滤波的问题,在对二维图像平滑去噪的过程中,采用基于中值滤波和提升小波变换相结合的图像去噪方法。在中值滤波基础上,构造基于脉冲检测的中值滤波器,找出混合噪声中脉冲噪声并进行滤波;与此同时,对原始小波进行提升,构造提升小波,然后采用提升小波阈值去噪方法抑制高斯噪声。实验结果表明：采用本文方法,混合噪声得到有效抑制,去噪效果好。     

基于改进差分盒算法的织物疵点自动检测方法

根据织物检测的实际情况需要,提出了基于差分盒算法的改进算法,在使用Brodatz纹理库样本的前提下,分别在盒子高度确定、盒子总数统计以及网格中盒子数量确定3个方面进行改进,在算法时间和精度两项上,对经典差分盒算法和改进算法进行了比较,对比得出了改进算法的时效性;还应用了改进差分盒算法对3种常见纹理的疵点织物进行了计算,以确认疵点织物,并验证了改进差分盒算法;实验通过检出率、误检率、漏检率和检测精度4个检测精度参数表明,改进的差分盒算法可以有效地区分疵点织物和正常织物,该方法具有很强的实用性。     

A Noisy SAR Image Fusion Method Based on NLM and GAN

The unavoidable noise often present in synthetic aperture radar (SAR) images, such as speckle noise, negatively impacts the subsequent processing of SAR images. Further, it is not easy to find an appropriate application for SAR images, given that the human visual system is sensitive to color and SAR images are gray. As a result, a noisy SAR image fusion method based on nonlocal matching and generative adversarial networks is presented in this paper. A nonlocal matching method is applied to processing source images into similar block groups in the pre-processing step. Then, adversarial networks are employed to generate a final noise-free fused SAR image block, where the generator aims to generate a noise-free SAR image block with color information, and the discriminator tries to increase the spatial resolution of the generated image block. This step ensures that the fused image block contains high resolution and color information at the same time. Finally, a fused image can be obtained by aggregating all the image blocks. By extensive comparative experiments on the SEN1–2 datasets and source images, it can be found that the proposed method not only has better fusion results but is also robust to image noise, indicating the superiority of the proposed noisy SAR image fusion method over the state-of-the-art methods.     

视觉掩盖效应下的无参考图像信噪比评价

 针对噪声图像,提出一种视觉掩盖效应下的无参考图像信噪比评价方法。采用Hosaka分块思想,利用四叉树分解,取消了Hosaka分块对图像尺寸的限制,分块的大小体现出块内图像的主要频率成分;然后检测各个子块噪声,根据图像的污染程度,计算NRPSNR值。利用LIVE Database Release2图像库中的WN的174幅图像检验NRPSNR与DMOS的相关度,并与MSE、PSNR以及HVSNR比较分析。实验结果表明,该方法总体评价效果优于其他3种评价方法,CC为-0.895 0,SROCC为-0.923 6,OR为0.042 9,主客观评价比较吻合,且对于其他噪声类型同样适用,体现了人的视觉掩盖效应,可以满足对无参考噪声图像进行准确可靠的质量评价要求。     

The study and application of a new filtering method on electronic speckle pattern interferometric fringe

It is important for the study of digital image processing to remove noises and enhance images because of various noises in images. The article is concerned with the recursive algorithm-filtering technique, which is capable of effectively removing noise and rapidly leading to a continuous gray-level distribution of a random image. By applying the method on speckle images of defects of rubber material, it is shown that this technique is the most effective and speedy method for the filtering of ESPI fringe patterns. Comparing the images before and after filtering, we can see the advantages of the novel technique clearly. It can increase the accuracy of measurement both in phase measurement and in quantitative evaluations of defects.     

基于相对微分计盒法的人造目标分形检测

对光电目标进行自动检测与识别是导弹末端智能制导的一项关键技术。基于图像分形维计算的相对微分计盒法,提出了一套实用的自然背景中人造目标的检测方法,给出了检测窗口与尺度选择的标准与参考值。大量实验证明,分形检测方法比传统的最大对比度检测方法稳定,是一种非常有前途的方法。     

噪声对数字图像相关法计算结果的影响研究

不同的散斑场会显示出不同的灰度分布特征,并对数字图像相关方法的计算结果有着重要影响。使用计算机模拟生成一系列单向拉伸图像和双向拉伸图像,并在生成的图像中添加噪声,从而获得一系列含噪声单向拉伸图像和含噪声双向拉伸图像。使用数字图像相关方法对无噪声图像和含噪声图像分别进行相关计算,并分析研究图像应变量与相关计算结果正确率间的关系,研究结果表明发现当图像的应变量在一定范围内时,数字图像相关方法计算结果的正确率较高。同时发现,当图像的应变量较小时,噪声对相关计算结果的影响较大,随着图像应变量的增大,噪声对相关计算结果的影响逐渐减小,当图像的应变量到达一定程度时,噪声对相关计算的影响就不明显了。     

Determination of skeleton and sign map for phase obtaining from a single ESPI image

A robust method of determining the sign map and skeletons for ESPI images is introduced in this paper. ESPI images have high speckle noise which makes it difficult to obtain the fringe information, especially from a single image. To overcome the effects of high speckle noise, local directional computing windows are designed according to the fringe directions. Then by calculating the gradients from the filtered image in directional windows, sign map and good skeletons can be determined robustly. Based on the sign map, single image phase-extracting methods such as quadrature transform can be improved. And based on skeletons, fringe phases can be obtained directly by normalization methods. Experiments show that this new method is robust and effective for extracting phase from a single ESPI fringe image.     

Speckle reduction by selective spatial-domain mask in digital holography

An improved method of using a selective spatial-domain mask to reduce speckle noise in digital holography is proposed.The sub-holograms are obtained from the original hologram filtered by the binary masks including a shifting aperture for being reconstructed. Normally, the speckle patterns of these sub-reconstructed images are different. The speckle intensity of the final reconstructed image is suppressed by averaging the favorable sub-reconstructed images which are selected based on the most optimal pixel intensity sub-range in the sub-holograms. Compared with the conventional spatial-domain mask method, the proposed method not only reduces the speckle noise more effectively with fewer sub-reconstructed images,but also reduces the redundant information used in the reconstruction process.     

融合改进直方图PDE和二维Tsallis熵多阈值SAR分割

针对合成孔径雷达(SAR)图像中存在大量的相干斑噪声，对SAR图像进行分割易出现分割不精、边缘模糊等问题，融合改进的直方图PDE和二维Tsallis熵多阈值，提出了一种SAR图像分割算法。根据PDE直方图均衡化方法，将图像去噪与图像增强加权融合，利用各自权值调整去噪项与图像增强项；同时将二维Tsallis熵单阈值分割方法扩展到多阈值分割, 建立基于多阈值的选取方法，并引入萤火虫算法来求解最优阈值对，实现了二维Tsallis熵多阈值对去噪增强SAR图像的有效分割。仿真结果表明:与其他3种分割算法相比，该文算法在处理噪声大、灰度差值小的图像时具有较高的分割精度，PRI至少提升2.53%、VOI降低8.48%、GCE降低11.14%。     

An effective method for reducing speckle noise in digital holography

An effective method for reducing the speckle noise in digital holography is proposed in this paper.Different from the methods based on classical filtering technique,it utilizes the multiple holograms which are generated by rotating the illuminating light continuously.The intensity images reconstructed by a series of holograms generated by rotating the illuminating light possess different speckle patterns.Hence by properly averaging the reconstructed intensity fields,the speckle noises can be reduced greatly.Experimental results show that the proposed method is simple and effective to reduce speckle noise in digital holography.     

Speckle noise attenuation in optical coherence tomography by compounding images acquired at different positions of the sample

This study demonstrates a simple method for attenuating the speckle noise generated by coherent multiple-scattered photons in optical-coherence tomography images. The method could be included among the space-diversity techniques used for speckle reduction. It relies on displacing the sample along a weakly focused beam in the sample arm of the interferometer, acquiring a coherent image for each sample position and adding the individual images to form a compounded image. It is proven that the compounded image displays a reduction in the speckle noise generated by multiple scattered photons and an enhancement in the intensity signal caused by single-backscattered photons. To evaluate its potential biomedical applications, the method is used to investigate in vitro a caries lesion affecting the enamel layer of a wisdom tooth. Because of the uncorrelated nature of the speckle noise the compounded image provides a better mapping of the lesion compared to a single (coherent) image.