基于形态学和OTSU算法的红外图像降噪及分割

为了在去除红外图像的脉冲噪声的同时,有效保持和恢复图像的边缘细节,提出了基于灰度特征和众数原则的迭代双边中值滤波方法。此方法根据脉冲噪声的灰度特征以及众数原则,将取最小和最大值、而在邻域的灰度分布上孤立的像素识别为噪声。根据基于空间距离和灰度相似的加权系数,对邻域中的无噪像素与已经去噪恢复的像素进行频次加权,用频次加权中值作为噪声像素的估计值。其中,以迭代遍历的方式执行去噪处理,充分利用前次遍历处理的结果,以去除高密度噪声。实验数据证明,此方法去噪所得的PSNR和EPI值以及视觉效果均优于现有方法,具有更好的去噪性能。     

Random-valued impulse noise removal using adaptive dual threshold median filter

Noise detection and its removal is very important in the image processing. Detection of noise is very crucial and significant in random valued impulse noise because it does not hamper the image pixels uniformly. This paper presents a novel and unique concept of adaptive dual threshold for the detection of random valued impulse noise along with simple median filter at noise removal stage. Simulation results shows that an efficient noise detection leads to a superior quality of de-noised image as compared to existing adaptive threshold based image de-noising techniques. Proposed threshold computation is based on averaging of pixel values of window which enhances the PSNR of our system as compared to existing median filter based image de-noising methods.     

Edge preserving adaptive anisotropic diffusion filter approach for the suppression of impulse noise in images

This paper proposes a new anisotropic diffusion approach to remove the impulse noise and retain the fine details. The proposed approach contains two stages, the first stage detects the impulse noise, and the second stage removes the noisy pixel and retains the fine details of the original image. The Laplacian operator is used to fine-tune the image quality of the restored image in the anisotropic diffusion filter. The proposed approach is tested with PSNR, IEF, correlation factor, and NSER for different test images and the results are compared against existing algorithms. The simulation results show that the proposed approach gives better results than the existing denoising algorithms.     

基于像素梯度自适应迭代中值滤波器的图像脉冲噪声抑制算法

图像脉冲噪声移除是获得高质量图像的关键。本文通过热红外相机成像原理研究,提出了一种基于像素梯度自适应迭代中值滤波器的图像脉冲噪声抑制算法。首先,根据相机的调制传递函数计算获取原始图像的最大像素梯度,继而建立相应的像素梯度集合。然后,计算原始图像与对应像素梯度滤波图像的梯度权重均方根误差集合,并将该集合高斯分布的最大值对应的像素梯度确定为最佳像素梯度。最后,根据图像中脉冲噪声的密度和复杂度,确定所提滤波器的自适应窗口大小和迭代次数。大量实验结果表明,所提滤波器对移除8位、16位的单通道脉冲噪声图像展现出良好的鲁棒性。与其它先进方法相比,该方法可以实时移除真实热红外相机采集图像中低密度的随机值脉冲噪声和SAPN,并实现噪声抑制过程中99.5%以上的原始像素不会遭受破坏。除此之外,针对高密度SAPN抑制,该方法获得了具有竞争力的结果,与运行时间较快的滤波方法相比表现出较好的PSNR和SSIM,与PSNR和SSIM较优秀的去噪方法相比表现出较快的运行时间。对于极限SAPN（99%）破坏的图像,也能够恢复有意义的图像细节。     

基于中值滤波器的红外图像噪声处理的改进方法

基于红外图像成像的机理和热像仪工作方式,红外图像往往混有大量随机噪声,而这些都是造成红外图像和视频质量下降的重要原因。中值滤波是一种常用的非线性的滤波方式,对于图像降噪有很好的效果。中值滤波器的处理窗口大小需要提前设定且在处理过程中不能改变。噪声密度越大需要处理窗口越大,但也导致图像的细节相应越模糊。综合窗口大小对降噪能力和细节处理能力的影响,文中对传统的中值滤波器算法进行改进。实验表明,在中值滤波器去除噪声的过程中,随着窗口图像噪声分布情况动态调整窗口大小,能够做到既尽可能去除噪声,又尽可能保持图片的细节,使图像处理整体效果得到提升。     

An effective 2-stage method for removing impulse noise in images

In this paper, a robust 2-stage impulse noise removal system is proposed to remove impulse noise from extremely corrupted images. The contributions are in two-fold. First, a neuro-fuzzy based impulse noise detector (NFIDET) is introduced to identify the noisy pixels. NFIDET is a powerful noise detector that can handle image corruption even up to 90% with zero miss and false detection rate with a simple neuro-fuzzy structure. This is the best result among the other impulse noise detectors in the literature. Second, this paper presents a new approach for weight calculation of adaptive weighted mean filter by using robust statistical model. An adaptive robust weighted mean (ARWM) filter removes a detected noisy pixel by adaptively determining filtering window size and replacing a noisy pixel with the weighted mean of the noise-free pixels in its window. A Geman–McClure robust estimation function is used to estimate the weights of the pixels. Simulation results also show that the proposed robust filter substantially outperforms many other existing algorithms in terms of image restoration.     

Similar neighbor criterion for impulse noise removal in images

In this paper, a new method is proposed for removing and restoring random-valued impulse noise in images. This approach is based on a similar neighbor criterion, in which any pixel to be considered as an original pixel it should have sufficient numbers of similar neighboring pixels in a set of filtering windows. Compared with other well known methods in the literature, this technique achieves superior performance in restoring heavily corrupted noisy images. Furthermore, it has low computational complexity, and equally effective in restoring corrupted color and gray-level images.     

一种用于抑制椒盐噪声的多窗口中值滤波器

该文提出了一种用于抑制椒盐噪声的多窗口中值滤波算法。算法在招待过程中根据具体情况采用不同大小的滤波窗口。仿真结果表明，与标准中值滤波算法相比，该方法不仅可以有效去除图像中的椒盐噪声，特别是在噪声密度非常大的情况下，表现了很好的性。     

An intensity independent fixed valued impulse noise detector for image restoration

Most of the impulse noise detectors used for detection of fixed valued impulse noise are effective only for salt and pepper or a band type noise occurring at the extreme ends of the allowed range of intensity levels. The performance of these detectors deteriorates drastically when fixed valued impulses occur anywhere within the allowed gray scale. In this paper, an impulse detection scheme is proposed which can effectively detect all types of fixed valued impulse noise and also differentiates between noisy and noise-free pixels of identical intensity levels. The improved performance of the proposed method is verified through extensive simulations for various fixed valued impulse noise models.     

脉冲噪声图像的中-均值滤波算法

由于在图像信息的获取和传输过程中,图像常常受到不同程度的脉冲噪声污染。为了有效地去除高浓度脉冲噪声,提出了一种基于中－均值滤波器的噪声去除算法。该方法根据脉冲噪声特点,设定一个简单的噪声检测算子,根据噪声检测结果设定自适应滤波窗口,同时根据噪声密度选择中值和均值滤波器。为了更加有效地保留图像的原有信息,对非噪声点不做滤波处理。仿真结果表明,所提出的中－均值滤波方法不仅能有效地去除高浓度的脉冲噪声,而且能很好地保留图像的原有信息,并具有较短的滤波处理时间。     

一种改进的自适应中值滤波算法研究

非线性滤波是一种有效的噪声抑制技术,得到了广泛的应用。文中针对标准中值滤波方法存在的不足,提出自适应中值滤波方法。该方法采用一定的检测标准对图像中的噪声点进行检测,并采用改进的中值滤波方法对噪声点进行滤波。实验结果表明,此方法较标准中值滤波具有更优良的滤波性能。     

一种改进的图像中脉冲噪声滤波方法

提出了一种估计脉冲噪声强度的方法,并针对传统中值滤波(MF)法在去除脉冲噪声时存在的不足,给出了一种由噪声检测和噪声滤波2个阶段组成的图像滤波方法.实验结果表明,采用本文估计方法获得的噪声强度偏差较小,噪声滤波方法能在有效去除噪声的同时保持图像的边缘.     

An efficient algorithm for the removal of impulse noise from corrupted images

In this letter, we propose an efficient algorithm, which can successfully remove impulse noise from corrupted images while preserving image details. It is efficient, and requires no previous training. The algorithm consists of two steps: impulse noise detection and impulse noise cancellation. Extensive experimental results show that the proposed approach significantly outperforms many other well-known techniques for image noise removal.     

Restoration of signals degraded by impulse noise by means of a low-distortion non-linear filter

A simple low-distortion non-linear filter for the restoration of signals degraded by random impulsive noise is proposed. It performs considerably better than a median filter, lowering the reproducing error both in mean-square and maximum-error sense, although being comparable in computing time and in terms of storage.     

一种基于极值的自适应中值滤波算法

图像平滑处理中,如何在去除噪声的同时完整地保留图像边缘细节一直是非线性滤波算法研究的热点问题。提出了一种基于极值的自适应中值滤波算法,该算法根据图像中某点是否为邻域极值点将全部像素分为可疑噪声与信号两类。对可疑噪声点采用包括八个一维窗口和一个二维窗口在内的不同尺度和不同方向的九个子窗口,按照各个子窗口的均方差大小,自适应选择窗口进行中值滤波;对信号点不加处理,灰度值不变。测试结果表明,该算法的滤噪特性和细节保护能力优于多级中值滤波;执行速度较快,优于经典中值滤波。     

Quaternion switching filter for impulse noise reduction in color image

A novel approach to impulse noise reduction in color image is introduced in this paper. By applying the quaternion unit transform theory, the difference between two color pixels can be represented in the quaternion form. Based on the difference mentioned above, an efficient filter that can switch between the vector median filter (VMF) and the identity filter (no filtering operation) is proposed. Extensive simulation result indicates that the proposed filter achieves a trade-off between noise suppression and detail preservation in both correlated and uncorrelated impulse noise scenarios when compared with other widely used filters. Furthermore, the computational complexity analysis shows that the proposed filter is quite efficient.     

改进自适应中值滤波算法研究

重点介绍了自适应中值滤波算法以及两种改进的自适应中值滤波算法.针对这3种滤波算法,对含有不同密度椒盐噪声的图像进行去噪实验.结果表明:改进算法去噪效果明显、能有效保护图像细节,PSNR保持在25 dB以上;改进算法在高密度噪声时也能得到细节较为清晰的图像,PSNR比改进前的提高17 dB以上.     

A new filter for the removal of random-valued impulse noise from highly corrupted images

In this paper, we present a new two-stage filter for the removal of random-valued impulse noise. The new filter identifies noise candidates by analyzing the amount of similar pixels in intensity value, and then reconstructs them by the total variation inpainting method. The experimental results are reported which show the efficiency of our method in removing random-valued impulse noise. Further, our filter can be used for image restoration from images damaged by the superimposed artifacts.     

基于PCNN噪声检测的两级脉冲噪声滤波算法

为有效滤除图像中严重脉冲噪声干扰,提出了一种基于改进型脉冲耦合神经网络(PCNN)噪声检测的两级脉冲噪声滤除算法。该算法首先利用PCNN同步脉冲发放特性区分定位噪声点和信号点位置,其次根据噪声点局部邻域信息对噪声进行第1级自适应滤波,然后再利用具有保护边缘细节特点的多方向信息中值滤波器(MF进行第2级辅助滤波。实验结果表明,该算法在噪声检测中无需设定检测阈值,噪声检测精度较高;在去噪过程中不但有效滤除噪声干扰,而且能很好地保护图像边缘细节等信息,具有较好的主观视觉效果和客观评价指标,比传统MF及其它相关算法有更优的滤波性能,去噪能力强、信噪比高和适应性好,特别是对受严重噪声污染的图像,显示了更大的优越性。     

基于噪声估计的自适应开关型中值滤波器

提出了一种基于噪声估计的自适应开关型中值滤波器(IASMNE,improved adaptive switching median filter based on noise estimation)。IASMNE以图像经小波变换后在不同尺度和不同方向提取的子带滤波系数值的统计信息构成刻画图像受噪声干扰程度的特征矢量,在大量噪声图像上获得的特征矢量为学习数据集,并利用支持向量回归(SVR)分析实现对图像中噪声比例的准确估计。基于此,IASMNE对高、中、低不同噪声比例图像启动不同的滤波策略,并灵活设置滤波参数。大量实验表明,与其它开关型滤波器相比,IASMNE能够合理地根据图像噪声干扰程度进行最佳滤波,尤其是对于大于70%的椒盐噪声(SPN)能够大幅度提高图像质量。