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传统的中值滤波和均值滤波通常被分别用来滤除椒盐噪声和高斯噪声.但是当图像同时存在高斯噪声和椒盐噪声时,单独使用哪种滤波方法都不会达到最好的去噪效果.为了能同时滤除两种不同性质的噪声,提出了一种新的自适应混合噪声滤波算法.该算法采用了一种基于自适应阈值的方法对滤波系数加以优化,使其既可以有效地减少噪声,又可以较好的保持图像的边缘细节信息,仿真结果表明该算法能较好的滤除混合噪声,且滤波效果优于传统的滤波算法. 相似文献
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目的为了提高激光三维成像系统中的图像质量,有效滤除图像中噪声,提出一种自适应均值漂移的图像滤波算法。方法在传统算法基础上对均值漂移滤波算法进行改进,选取领域内像素的均方差为控制参量对带宽矩阵h大小进行自适应调控。根据宽带矩阵h的大小,选择合适的像元值参与到计算均值过程中,以提高结果的计算精度。结果实验结果表明改进后的算法能够有效滤除图像中的噪声,提高图像清晰度。结论该算法具有良好的保边去噪特性。 相似文献
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当有参考噪声信号时,自适应噪声抵消的实质就是求参考噪声输入通路的逆滤波器,LMS自适应滤波问题就是一个多变量函数的极值问题。LMS算法因其具有算法简单,容易实现的优点而为常用,但是算法的收敛特性和失调量受到步长参数μ的影响。而步长参数μ和最优值不易确定。遗传算法是一种应用于大规模搜索空间的有效方法,它不要求函数的解析表达式,只根据已知的测量数据便可以求得全局极值。本文以FIR滤波器为例。采用改进的实值编码遗传算法,将遗传算法用于逆滤波器的求解。计算机仿真结果表明该算法对噪声抵消取得了较满意的效果。 相似文献
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基于阈值判断的自适应中值滤波算法 总被引:1,自引:0,他引:1
针对标准的中值滤波算法在去除噪声与保留图像细节方面难以取舍的缺陷,在自适应中值滤波算法的基础上提出了一种改进的基于噪声点检测的自适应中值滤波算法.该算法在进行噪声点检测时采用了一种阈值判断法,充分利用了当前像素点与邻域像素点的灰度值之间的关系.结果表明,在噪声浓度较高时仍然可以区分噪声点与边缘点,滤波的同时有效地保护了图像的细节. 相似文献
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噪声概率快速估计的自适应椒盐噪声消除算法 总被引:1,自引:0,他引:1
提出一种可识别噪声概率自动调节滤波窗口的自适应椒盐噪声消除算法。对非理想椒盐噪声污染图像随机区域进行变窗口中值滤波,将结果与滤波前比对获得噪声点数,滤波区域即按此点数排序。然后取每种滤波窗口下的中间三组数据,该数据平均加权获取图像噪声概率初估计,对初估计平均加权即得图像噪声概率。滤波前首先采用阈值法排除明显噪声点,剩余像素中再以离窗口中心像素距离平方的倒数为权值估计中心像素。最后由噪声概率按照T-S模糊规则对不同模型的输出估计值进行融合。实验证明,与传统中值滤波等算法相比,该算法具有噪声自动估计和自适应窗口调节能力,滤波后标准均方差可减少20%以上,速度可提高一倍多。 相似文献
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We introduce a new nonlinear filter for signal and image restoration, the hybrid order statistic (HOS) filter. Because it exploits both rank- and spatial-order information, the HOS realizes the advantages of nonlinear filters in edge preservation and reduction of impulsive noise components while retaining the ability of the linear filter to suppress Gaussian noise. We show that the HOS filter exhibits improved performance over both the linear Wiener and the nonlinear L filters in reducing mean-squared error in the presence of contaminated Gaussian noise. In many cases it also performs favorably compared with the Ll and rank-conditioned rank selection filters. 相似文献
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Rastislav Lukac Konstantinos N. Plataniotis Anastasios N. Venetsanopoulos 《International journal of imaging systems and technology》2005,15(5):236-251
Noise suppression in multichannel data sets, such as color images, has drawn much attention in the last few years. An issue of paramount importance in designing color image filters is the determination of the coefficients that should be used to weight the inputs to the filter. In this study, we propose an evolutionary computation‐based approach to select and optimize the coefficients in the class of weighted vector directional filters. Using a genetic algorithm, we were able to adapt the filter weights to match varying image and noise characteristics. Extended experimentation with realistic image processing applications, including television image enhancement and virtual restoration of artworks, indicates that the proposed filters are capable of removing noise while preserving chromaticity information, edges, and fine details, as well as structural image content. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 236–251, 2005 相似文献
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Ali Abbasian Ardakani Afshin Mohammadi Fariborz Faeghi U. Rajendra Acharya 《International journal of imaging systems and technology》2023,33(2):445-464
Noise corrupts ultrasound images and degrades spatial and contrast resolutions. Hence, it is challenging to characterize the lesions precisely using ultrasound images. The present study aims to evaluate 67 denoising filters and select the best one for ultrasound image denoising. Seven test images were synthesized to evaluate the performance of filters at three different noise levels. Eleven full-reference quantitative image quality metrics (IQMs) were employed to evaluate the performance of the filters. A new filter evaluation method, Rank Analysis, was introduced and utilized at each noise level. The ten best filters with the smallest mean rank in all noise levels were defined for further analysis on real ultrasound images. The Rank Analysis was also employed for real ultrasound images, and filters were evaluated based on 14 IQMs (11 full-reference and three no-reference). Finally, the best filter was defined using the repeated measures analysis statistical test. According to the Rank Analysis results, the Spatial correlation (SCorr) filter obtained the best results with the mean rank scores±SD of 1 ± 0, which was significantly better than the other nine filters (p < 0.001). The second-best results were achieved by three filters, Bitonic, most homogeneous neighborhood, and Lee diffusion (p < 0.05). We concluded that SCorr is the best filter for ultrasound image denoising. It can be used in the pre-processing step before segmentation and diagnostic procedures. In addition, a new filter evaluation method, Rank Analysis, was introduced in this study, which is easy to use, fast, and provides reliable results. So, it can be used to evaluate newly developed filters in the future studies. 相似文献
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闪光CCD图像的中值-非线性扩散滤波 总被引:3,自引:0,他引:3
根据闪光CCD图像的特点,提出了一种中值-非线性扩散滤波(Median-NonlinearDiffusionFiltering,简称MNDF)方法。该方法采用中值预滤波来估计图像的真实边缘,通过求解偏微分方程(PartialDifferentialEquation,简称PDE)来进行非线性扩散滤波,充分发挥了中值滤波和非线性扩散滤波的优势,能更好地消除噪声、保护边缘。实验结果表明,在高斯噪声和脉冲噪声同时存在的情况下,MNDF方法取得的滤波效果较P-M方案和Catte方案要好,信噪比改善因子提高3~5倍,均方误差减小1.3~2.7倍。对闪光照相CCD图像取得了很好的消噪声结果,保护了边缘信息。 相似文献
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The state-of-the-art universal steganalysis method, spatial rich model (SRM), and the steganalysis method using image quality metrics (IQM) are both based on image residuals, while they use 34671 and 10 features respectively. This paper proposes a novel steganalysis scheme that combines their advantages in two ways. First, filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods. In addition, a total variant (TV) filter is also used due to its good performance of preserving image edge properties during filtering. Second, due to each type of these filters having own advantages, the multiple filters are used simultaneously and the features extracted from their outputs are combined together. The whole steganalysis procedure is removing steganographic noise using those filters, then measuring the distances between images and their filtered version with the image quality metrics, and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine. The scheme can work in two modes, the single filter mode using 9 features, and the multi-filter mode using 639 features. We compared the performance of the proposed method, the SRM and the maxSRMd2. The maxSRMd2 is the improved version of the SRM. The simulated results show that the proposed method that worked in the multi-filter mode was about 10% more accurate than the SRM and maxSRMd2 when the data were globally normalized, and had similar performance with the SRM and maxSRMd2 when the data were locally normalized. 相似文献
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The presence of zero-order diffraction and a conjugate image in digital holography essentially diminishes the quality of the reconstructed image. In this paper, a novel method that adopts numerical operation to eliminate the zero-order diffraction and conjugate image is presented. The whole process needs only one hologram and a complex finite impulse response (FIR) digital filter. The method of numerical elimination is simple; it filters the hologram directly in the spatial domain instead of in the frequency domain. The design of a complex finite impulse response filter is described in detail. The experimental results demonstrate that the operation can completely eliminate the zero-order diffraction and conjugate image and significantly enhance the quality of the reconstructed image. 相似文献
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We discuss and implement a log-polar transform-based distortion-invariant filter for automatic target recognition applications. The log-polar transform is a known space-invariant image representation used in several image vision systems to eliminate the effects of scale and rotation in an image. For in-plane rotation invariance and scale invariance, a log-polar transform-based filter was synthesized. In cases of in-plane rotation invariance, peaks shift horizontally, and in cases of scale invariance, peaks shift vertically. To achieve out-of-plane rotation invariance, log-polar images were used to train the wavelet-modified maximum average correlation height (WaveMACH) filter. The designed filters were implemented in the hybrid digital-optical correlation scheme. It was observed that, for a certain range of rotation and scale differences, the correlation signals merge with the strong dc. To solve this problem a shift was introduced in the log-polar image of the target. The use of a chirp function for dc removal has also been discussed. Correlation peak height and peak-to-sidelobe ratio have been calculated as metrics of goodness of the log-polar transform-based WaveMACH filter. Experimental results are presented. 相似文献