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图像平滑主要是为了消除噪声。噪声并不限于人眼所能看的见的失真和变形，有些噪声只有在进行图像处理时才可以发现。图像的常见噪声主要有加性噪声、乘性噪声和量化噪声等。图像中的噪声往往和信号交织在一起，尤其是乘性噪声，如果平滑不当，就会使图像本身的细节如边界轮廓、线条等变的模糊不清，如何既平滑掉噪声有尽量保持图像细节，是图像平滑主要研究的任务。-image smoothing is mainly to eliminate noise. Noise is not confined to the human
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NAME:
bpass
PURPOSE:
Implements a real-space bandpass filter which suppress
pixel noise and long-wavelength image variations while
retaining information of a characteristic size.
CATEGORY:
Image Processing
CALLING SEQUENCE
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Deblurring Images Using a Regularized Filter
This example shows how to use regularized deconvolution to deblur images. Regularized deconvolution can be used effectively when constraints are applied on the recovered image (e.g., smoothness) and l
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用卡尔曼滤波器处理图片，图片是进行加性白噪声的，输出进过处理的图片和原图片-Using kalman filter to deal with pictures, picture is for additive white noise, the output in processing of images and the original image
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在matlab平台上，使用多尺度curvelet变换，对SAR图像的相干斑噪声进行抑制，
先将图像进行对数变换，把相干斑乘性噪声转换为加性噪声，然后使用一种有效的阈值去噪方法，很好的抑制了相干斑噪声，效果不错。(On the MATLAB platform, the multiscale curvelet transform is used to suppress the speckle noise of the SAR image.
First, transform the image t
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