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。     

模糊权值中值滤波的X射线图像消噪算法

针对X射线荧光图像的低亮度及噪音造成的对比度差和图像模糊的问题,提出了一种模糊权值中值滤波的图像消噪算法.先用模糊邻域检测法结合梯度检测法分离原始图像中的噪音点与非噪音点,然后在噪音点的邻域内,计算各像素点与邻域中值的模糊相似度,用相似度作中值的权值,对噪音点邻域进行加权滤波;这种算法使图像的非噪音点保持不变.实验结果表明,本文算法不仅具有较强的消噪能力,而且能够保持图像的边缘细节和纹理信息.     

模糊权值中值滤波的X射线图像消噪算法

针对X射线荧光图像的低亮度及噪音造成的对比度差和图像模糊的问题,提出了一种模糊权值中值滤波的图像消噪算法.先用模糊邻域检测法结合梯度检测法分离原始图像中的噪音点与非噪音点,然后在噪音点的邻域内,计算各像素点与邻域中值的模糊相似度,用相似度作中值的权值,对噪音点邻域进行加权滤波|这种算法使图像的非噪音点保持不变.实验结果表明, 本文算法不仅具有较强的消噪能力,而且能够保持图像的边缘细节和纹理信息.     

一种基于特征块匹配的电子稳像方法

提出一种基于特征模块匹配的图像稳定的算法.该算法自适应地搜索图像特征模块进行后续稳像操作.在稳像过程中,提出一种图像特征匹配的快速算法,匹配得到局部运动矢量,然后对匹配结果进行一致性检验,最后采用可变窗口宽度的均值滤波法对图像序列运动轨迹滤波.试验表明,该算法有效地稳定了图像序列,并且满足实时性要求.     

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 %。     

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。     

基于圆边响应离焦估计的望远物镜自动调焦方法

本文提出了一种基于圆边响应曲线的离焦估计新算法,实现了调焦参数的标定和望远物镜的自动调焦。建立了圆形边缘的灰度响应与离焦半径的关系模型,设计了圆四周离焦半径的双阈值均值滤波器,实现了模糊图像离焦半径的精确估计,降低了运动模糊和噪声的影响。根据离焦半径与调焦距离的线性关系,采用折线拟合方法,求解正焦调焦距离。然后,利用多个物距和正焦像距,优化求解测距调焦模型参数,实现了成像系统的自动调焦。仿真和实际实验验证了离焦半径估计算法的有效性和鲁棒性。标定后的自动调焦成像系统图像清晰,拍摄距离在43～52 m之间的物理分辨率接近理论值的一半,可分辨线宽优于0.354 mm.     

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.     

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.     

基于几何代数的彩色光流场计算

提出了一种新的基于几何代数的彩色光流场计算方法.从新的角度出发讨论了运用几何代数的概念来解决彩色图像序列的可行性和简便性.在几何代数域内对彩色图像序列用多重矢量表示,证明了彩色光流场分析时进行约束条件时的测量问题,通过多重矢量而非多通道的图像处理方法来表示图像连续特性,从而扩大了测量范围;然后依据物体色彩在运动过程中保持不变的原理,在几何代数域内推导了彩色图像序列的光流约束方程及其解法.结果表明,该算法能够显著提高各种情况下的彩色光流场计算能力.     

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.     

低信噪比环境下的实时聚焦方法研究

低信噪比环境下,人们运用中值滤波与维纳滤波等作为图像预处理手段获得了一定的效果,但是图像预处理严重地影响了对焦速度。在低信噪比环境下所提出的避开图像预处理的最佳自动对焦方案为:首先,采用HSI分析法把RGB彩色图像转换为亮度信号;其次,利用能量梯度算子作为图像评价函数;最后,运用爬山算法控制策略进行自动对焦。结果表明,此方案的运算时间优势非常明显,对焦准确度最佳,可满足实时对焦系统的对焦速度与对焦准确度的要求。     

时域递归滤波对微光成像视距影响的研究

 针对微光成像中噪声较大及视距较短的问题,提出了一种自适应时域递归滤波算法。该算法通过自动调节时域递归的滤波系数来提高信噪比和延伸视距。实验显示当滤波系数分别为0.50、0.75和0.875时,视距分别能延伸至原始的1.73倍、2.64倍和3.87倍,所得到的视距延伸与理论值基本保持一致。实验结果表明该算法在保持图像运动部分清晰的同时,还能有效地消除噪声并延伸微光成像系统的视距。     

相干激光雷达距离像的噪声抑制算法研究

激光雷达能同时成距离像和强度像,较其他的成像体制给出更多的有用信息。距离像的去噪是激光雷达图像处理的关键步骤,去噪的好坏直接关系激光雷达在跟踪、定位等方面的精确性。根据距离像噪声来源,采用结合强度像的多级中值滤波对实际的雷达图像进行了去噪处理。首先利用强度像3×3邻域均值和图像平均值消除失落信息影响,然后采用多级中值滤波消除逸出值。分别给出了各步处理结果,最终获得了较清晰的距离像。研究结果表明运用结合强度像的多级中值滤波方法能够有效地抑制相干激光雷达距离像的噪声。     

Application of the vector ε and ρ extrapolation methods in the acceleration of the Richardson-Lucy algorithm

The vector ε and ρ extrapolation methods are applied in accelerating the convergence of the Richardson-Lucy (R-L) algorithm and its damped version. The theory and implementation are discussed in detail, and relevant numerical results are given, including the cases of noise-free images and images corrupted by the Poisson noise. The results show that the vector ε and ρ extrapolations of 9 orders can speed the convergence quite efficiently, and the ρ(9) method is more powerful than the ε(9) method for noisy degraded images. The extra computation burden due to the extrapolation is limited, and is well paid back by the accelerated convergence. The performances of these two methods are compared with the famous automatic acceleration method. For noise-free degraded images, the vector ε(9) and ρ(9) methods are more stable than the automatic method. For noisy degraded images, the damped R-L algorithm accelerated by vector ρ(9) or automatic methods is more powerful, and the instability of the automatic method is restrained by the damping strategy. We explain the instability of the method in accelerating the normal R-L algorithm by the numerical noise due to its frequent applications in the run.     

一种基于图像清晰度函数的调焦机构限区间变速控制方法

针对自动聚焦耗时长的问题，通过对调焦过程中图像清晰度的变化规律进行分析，在调焦范围内确定了有效区间，根据清晰度变化斜率调整驱动速率，改进并实现了一种调焦机构限区间变速控制方法。与常规的控制方法相比，本文方法具有行程短、速度快和精度高的优点。实测结果表明，该方法最短聚焦时间小于1.5 s，可以作为同类光学镜头通用的自动调焦控制方法。     

一种改进的Sobel梯度函数自动对焦评价算法

传统的自动对焦梯度函数评价算法在对细胞显微图像进行对焦时,由于对焦精度不佳,图像受噪声的影响较大。针对此问题,通过对不同对焦评价函数性能进行对比,提出了一种基于Sobel梯度函数改进的自动对焦评价算法——Sobel4direction_Brenner梯度函数算法。对对焦评价技术设计指标和算法的通用性进行了验证,结果表明:在调焦时该算法较传统对焦梯度函数能更好的抑制噪声,并且使电机在爬山算法的搜索对焦中具有更小的对焦搜索区间范围,获得的细胞显微图像的清晰度评价值也更高。     

Correlation recognition for range image of laser radar

The target recognition of laser radar becomes hot research in recent years, because laser radar can produce high space resolution and collect rich target information, such as range image, intensity image and Doppler image. In the vertical detection of laser radar, the problem of in-plane target rotation invariance is firstly solved. In the paper, a new support vector machine (SVM) correlation filter is presented, which simultaneously has the attractive attributes of SVM and common correlation filter. Exploiting the idea of margin of separation maximization, the design criterion is produced. The filter is synthetic by the multiple training images which are generated by rotating one image. The real range images of laser radar are used to finish the correlation experiments. The results show that the filter is not sensitive to the noise, the correlation peak is changed slightly for the different testing images, and the precision of location is high.This design way can be used in other recognition fields.     

Color image edge detection method using VTV denoising and color difference

The traditional Canny edge uses Gaussian filter to suppress the noise, it also smoothes out the image edges. An improved Canny edge detection method for color image is proposed in this paper, the improved method uses fast vectorial total variation (VTV) minimization model to remove noise in color image, and then calculates the color difference and direction in CIELAB color space, which is used for non-maximal suppression. Finally, the improved method extracts the edges by the double-threshold method. The experimental results show that the proposed method achieves better performance than the traditional Canny edge detector. It can remove noise while preserving the image edges, and effectively detect the image edges.     

对数似然图像分割的快速主动轮廓跟踪算法

针对跟踪目标尺度变化问题,提出了基于灰度对数似然图像分割的快速主动轮廓跟踪算法。改进的主动轮廓跟踪算法将根据以目标与背景的颜色差异而建立的对数似然图对图像进行阈值分割和数学形态学处理,再将Kalman滤波器结合到主动轮廓跟踪算法进行目标跟踪。改进的主动轮廓跟踪算法对目标分割准确,轮廓特征显著,跟踪效果稳定,算法能很好地适应跟踪目标尺度变化。通过Kalman滤波器对目标位置点的预测减少了主动轮廓跟踪算法收敛的迭代次数,使算法的运算效率提高了33%左右。