共查询到18条相似文献,搜索用时 62 毫秒
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WangBaoping FanJiulun XieWeixin WuChengmao 《电子科学学刊(英文版)》2004,21(4):306-313
A novel filter for image restoration is proposed in this paper. The filter estimates histogram of original image via input image. It gets a membership function through the histogram, and the membership function contains a lot of information of original image. Then a weighted fuzzy mean filter is established based on this membership function; meanwhile, the filter adaptively adopts different filter scale according to the character divergence of image region and intensity of impulsive noise. Experimental result shows that new filter gives superior performance to conventional filters and currently used fuzzy filter. 相似文献
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基于空间分布的红外图像直方图均衡算法 总被引:3,自引:0,他引:3
随着非制冷焦平面阵列(UFPA)红外探测器的日益成熟,红外热成像技术越来越广泛应用于公安、消防、军事、医学、监控等领域。红外图像直方图分布集中,对比度低并通常伴有大量散粒噪声,需要处理以改进视觉效果。文中提出一种基于空间分布的图像直方图均衡算法,在图像增强同时又适当抑制噪声提升,实验表明该算法优于HE、PE、HP等算法,并具有较快的计算速度。 相似文献
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高概率椒盐噪声对数字图像的重度污染大量存在,如要消除信息少且噪点集中的噪声存在诸多困难;而低概率椒盐噪声对数字图像的轻度污染虽然可完全滤除,但在实际图像恢复中又缺少普遍意义.本文基于灰度值空间的模糊划分和描述灰度水平的模糊数,采用极值法对高概率噪声实施检测并建立恰当滤波窗口,应用广义重心去模糊化法和非噪声点对应的隶属函数设计一种新模糊滤波器.最后,通过仿真实例获得该滤波器可有效地过滤数字图像中高概率椒盐噪声,并说明它的去噪性能优于其他常见滤波器. 相似文献
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在医学图像处理、遥感图像处理、图像修复等图像处理中,总希望能得到清晰的图像,从而更准确的理解对象的特征。但在实际过程中由于环境和系统本身的缺陷,通常捕获到的图像总是和受到不同程度噪声污染,因此如何去除图像中的污染噪声就成了图像预处理中的重要步骤[1]。本文以Matlab语言为基础用各种方法对图像进行去噪处理,并且对于处理结果进行比较、分析,从而得出各自的特点以备在图像处理中可以方便的选择。 相似文献
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JIANG Bo HUANG Wei 《中国电子科技》2007,5(1):70-74
Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter (ATMF) has been developed by combining the adaptive median filter (AMF) and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter. 相似文献
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基于自适应滤波的噪声抵消法 总被引:4,自引:1,他引:4
语音降噪就是从带噪语音信号中提取尽可能纯净的原始语音。文中介绍了一种基于自适应滤波的噪声抵消法,采用归一化最小均方误差算法,采集实际噪声环境下各种不同信噪比的带噪语音样本进行降噪处理,实验结果表明,处理后信号的信噪比得到了较大程度的提高,大大改善了听音效果,具有很高的可懂度,且语音自然度好,没有失真;并与谱减法进行了比较,自适应噪声抵消法的降噪幅度比谱减法有一定提高,在听音效果上,用自适应噪声抵消法处理后的语音在清晰度、自然度方面优于谱减法。 相似文献
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基于颜色直方图的图像检索技术 总被引:1,自引:1,他引:1
使用颜色空间分布熵来表示图像的颜色空间分布特征,结合图像的颜色直方图特征,采用加权综合法和比例系数法表示图像的综合特征,设计了基于颜色直方图和图像空间分布熵的图像检索算法.利用查全率和查准率对算法进行了评价.通过实验分析比较可知,所设计的方法具有较好的查准率和查全率. 相似文献
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Dong‐Ho Lee 《ETRI Journal》2012,34(4):564-571
This paper presents an algorithm for removing high‐density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line‐weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image. 相似文献
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针对灰度图像受脉冲噪声污染后的恢复处理问题,提出了一种改进的自适应中值滤波算法。该方法根据脉冲噪声的分布特点,采用极大值、极小值和领域均值判定准则进行噪声点的检测,然后用检测窗口内最小非噪声点集合的中值作为噪声点的滤波输出。实验结果表明,与其他几种算法相比,文中算法不仅在峰值信噪比(Peak Signal to Noise Ratio)和结构相似度(Structural Similarity,SSIM)上有较大优势,而且还具有较低的时间复杂度和更好的自适应性。也进一步说明该方法不仅能有效地检测并滤除噪声点,还能较好地保护图像的边缘细节。 相似文献
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针对带有高斯噪声和椒盐噪声两种混合噪声的红外图像,提出了一种自适应加权混合去噪算法。该算法首先通过邻域像素的灰度差值来判断像素噪声的类别,然后对高斯噪声采用自适应加权均值滤波法滤除,对椒盐噪声采用自适应加权中值滤波算法滤除。实验表明,该方法优于传统均值滤波算法和中值滤波算法,能同时消除混合噪声,并具有较好的保护图像细节的能力。 相似文献