改进的中值滤波算法在图像去噪中的应用

 针对标准中值滤波方法存在的不足,结合均值思想提出两种改进的中值滤波算法,即加权快速中值滤波算法和加权自适应中值滤波算法,MATLAB实验证实两种方法均能更好地保存原始图像的细节和边缘。比较两种新方法得出以下结论：加权改进中值滤波算法对低密度的脉冲噪声去噪效果明显,对于高密度脉冲噪声去噪效果不理想,但能大大提高中值滤波的运行速度,对数字图像实时处理意义很大;加权自适应中值滤波算法能够有效地消除被污染图像中的高密度脉冲噪声,较标准中值滤波具有更优良的滤波性能,较加权快速中值滤波算法在去噪方面有更好的鲁棒性。     

闪光照相CCD图像的自适应中值滤波方法

中值滤波是一种在去除噪声的同时能较好地保护图像边缘细节的非线性图像处理方法。为了滤除闪光照相CCD图像中的脉冲噪声，同时能更好地保护图像边缘，提出了一种改进的自适应中值滤波方法。该方法采用局部中值和局部方差作为判断噪声点的阈值，实现了局部自适应的中值滤波，克服了传统自适应中值滤波方法的缺点，对椒盐噪声和随机脉冲噪声均有较好的滤波效果。实验结果表明，该方法消除图像脉冲噪声十分有效，对闪光照相CCD图像的处理结果也较好。     

QR码图像预处理中的滤波研究

QR码图像采集过程中会出现椒盐噪声,为了在滤除图像椒盐噪声的同时能很好地保持图像的细节,将几种常用中值滤波方法应用到QR码的图像预处理中,进一步对其结果进行比较,得出QR码图像中值滤波的规律。据此提出利用窗口系数的新中值滤波方法,先二值化,然后进行基于滤波窗系数的中值滤波处理,经过实验比较找到一组系数。实验结果表明:将该系数的中值滤波用在QR码图像预处理中可以大大提高译码的效率和准确率。在加噪一定情况下,实验的识别率达到了100%。     

视频车辆监控系统图像滤波算法的研究

视频车辆监控系统中图像噪声对背景学习、车辆识别等具有很大影响,已有滤波算法又难以满足系统对滤波效果和速度的综合要求。通过对比不滤波、采用中值滤波或均值滤波时的车辆识别效果和速度,选用均值滤波作为进一步的研究对象。在适当减少计算量的基础上,通过改进数据访问方法和计算方法进一步提高了算法速度,并用Visual C++ 6.0实现了该算法。实验表明,新算法的速度比盒滤波提高了55 %。     

一种有效的红外小目标检测方法

提出了一种基于中值滤波与梯度法的红外小目标检测方法.该方法首先通过中值滤波对红外图像进行平滑处理,接着采用背景差分技术将原始图像与经过中值滤波后的图像进行差分对消.在此基础上,再使用梯度锐化法对残差图像进行边缘信息的增强.最后,利用二值化处理凸显出目标点.该方法通过中值滤波与梯度法的互补效应实现了红外小目标的有效检测,仿真实验结果证明了该算法的有效性.     

一种新的激光雷达距离像噪声抑制方法

主要针对激光雷达距离像的距离反常噪声抑制问题,阐述了激光雷达距离像的噪声原理,分析了应用传统中值滤波方法抑制距离反常噪声的缺陷,提出了基于包围准则的自适应中值滤波算法。该方法首先根据包围准则检测噪声,对5×5滤波窗口内的像素值进行排序差分;然后选择低于门限长度最长的连续差分值对应的像素值作为距离正常值;最后运用中值滤波和加权均值滤波进行噪声抑制。实验结果表明,该方法有效抑制了距离反常噪声,且较好地保护了距离图像中目标的边缘细节,均方根误差分别比3×3和5×5窗口中值滤波法减少了27.1%和9.1%。     

基于边缘特征的中值滤波的小目标检测法

提出了一种基于边缘特征调整滤波尺寸的中值滤波算法用于小目标的检测。以图像像素的四个方向的边缘分量确定阈值,以此阈值判断像素是否为小目标区域,在此基础上调整滤波尺寸,采用中值滤波方法检测出小目标。结果表明,该算法对于小目标检测有很好的效果。     

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。     

提高三维激光扫描系统图像质量技术的研究

对其中三维激光扫描图像处理的关键技术———二值化、细化以及离散数据点云的滤波进行了研究,提出了一种先加权中值滤波,然后再小波分析滤波的新的降噪方法,并通过遗传算法对权重值进行了优化。在通常情况下,由于小波分析计算工作量大,所以提出了一种相对简单的算法,实现了在单台PC机上的运算。     

THz激光主动图像预处理方法研究

鉴于THz激光主动成像以其较低的光子能量和较高的穿透能力在危险品检测、医疗和食品检验等领域有着广泛的应用前景,将对比度拉伸变换、中值滤波和均值滤波常规图像预处理方法引入到THz激光主动图像处理中,对五元人民币纸币的水印THz面阵图像进行了预处理。处理结果表明,对原始图像进行对比度拉伸变换可以较大地提高图像对比度,在此基础上进行的中值滤波和均值滤波可进一步提高图像的辨识能力,中值滤波可以保护目标边缘细节并使图像平滑。在对比中发现,当窗口大小为9×9像元时滤波后的视觉效果最佳。     

Random-valued impulse noise removal by the adaptive switching median detectors and detail-preserving regularization

This paper firstly proposes an adaptive non-local switching median filter. Then, a two-phase scheme is presented to remove the random-valued impulse noise. In the first phase, the adaptive switching median filter or the adaptive non-local switching median filter is used to identify the pixels which are likely to be the noise candidates. In the second phase, only the noise candidates’ values are restored by a detail-preserving regularization method. Simulation results show that the proposed method is significantly superior to some of the state-of-the-art methods.     

Switching non-local vector median filter

This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.     

Fast frequency modulation optical code division multiple access communication system

An optical fast frequency modulation code division multiple access communication system is proposed. In this system, an electrically controlled tunable optical filter (TOF) is used to encode the modulated broadband light source. The code depends on the function set to the controller. Two-dimensional code named functional code is also proposed based on a shifted sine function. The function defines the dynamic coding pattern of the central wavelength of the transmitted narrowband optical signal. Thus, the system will allow for an easy reconfiguration of the transmitter without the need for sophisticated encoder. At the receiver, a synchronized TOF with the same function is used as a decoder. The performance of this system is shown to be better compared with a fast frequency hopping and a spectral amplitude coding systems.     

Minimum spanning tree-based random-valued impulse noise detection for a switching median filter

A switching median filter is effective for impulse noise elimination while preserving edges and details of an image. In the switching median filter an impulse noise detector is employed before filtering, and the detection result is used to control whether a pixel should be filtered or not. However, the conventional impulse detector tends to misjudge noise-free pixels constructing line structures to be the noises. We propose a new random-valued impulse noise detector based on the minimum spanning tree, and it is applied to the switching median filtering to eliminate the impulse noise effectively even for the image including line structures. Through the experiments, the effectiveness of the proposed random-valued impulse noise detector is illustrated.     

一种改进的基于分水岭的图像分割算法

针对分水岭算法过分割现象,提出一种综合分水岭算法、中值过滤算法和归一化割算法的改进算法。该算法首先应用改进型的中值过滤算法对图像进行适当的除噪;然后通过分水岭变换对图像进行了初步分割,最后使用归一化割算法进行图像精度分割。算法集合了分水岭算法、中值过滤算法及归一化割算法的优点,既较好地解决了分水岭算法中过度分割的问题,又降低了归一化割算法的时间复杂度。实验结果表明该算法是一种切实可行的图像分割方法。     

Adaptive filter for unwrapping noisy phase image in phase-stepping interferometry

An adaptive filter for preprocessing wrapped phase image with high noise content has been developed. The window size of this median filter is adjustable according to its location in the noisy phase image. This size-adjustable median filter has not only high noise-rejection ability, but also both good phase-jump identification and image-detail preservation properties. Phase unwrapping can then be done to recover the real phase image without the hampering influence of noise, especially the noise near the phase jumps. Both numerical simulation and experimental results used to examine the effectiveness of this adaptive filter are presented.     

Two-way code translation by computer-generated holographic filters

In two-way code translation, we want to design a single holographic filter that can work in two directions: It converts one specific image into a second associated image, and it can also convert the second image into the first image. Such a filter could be used perhaps as an associative memory. To generate the filter phase properly for the two filtering processes, we can use two complex conjugate filter functions, as they are incorporated automatically in a holographic filter. The filter amplitude cannot in general be made exactly correct for both filtering processes. We investigated different error criteria for the optimization of the filter amplitude, with and without noise in the input. Computer simulations are shown.     

基于同态滤波的遥感薄云去除算法

目前常用的遥感薄云去除法是同态滤波法,但由于所采用的滤波器的局限性,传统的同态滤波法只能去除处于低频区域的云,而对处于高频区域的云则没有处理效果。因此在研究传统同态滤波算法,选取性能最佳的频域滤波器对图像进行处理的基础上,引入了空域3×3中值滤波,用像素点3×3邻域内9个像素点的中值来代替该点的像素值,旨在对前者无法去除的高频突变云区进行处理。而后结合主观视觉和客观统计分析两方面对仿真结果进行评价,经分析表明,用该方法处理过的影像在信息未受损失的情况下,高频突变云有所减少,达到了预期目的。     

层析三维数字化仪层析图像滤波器的设计及研究

提出一种新型的递归中值滤波器，抛掉了统计参数的制约，将滤波算法转化为一种优化处理。该方法兼顾了滤波处理的光滑连续性及抑制噪声的累积特性，可有效地消除脉冲型干扰的影响，同时也从理论的角度上对该算法进行了分析。为消除加性高斯噪声，提出了一种基于图像边缘方向的小波线性滤波器，它仅仅处理边缘信息。该算汉的极大优点是克服了边缘模糊效应，小波的去噪逆向重构的处理方法对边缘为跃型的层析图象非常实用。