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用不同的核进行图像的二维滤波
函数cvSmooth实现各种方法的图形平滑。
一般来说,图像平滑主要是为了消除噪声。图像的常见噪声主要有加性噪声、乘性噪声和量化噪声等。由于图像的能量主要集在低频部分,而噪声所在频段主要在高频段,因此通常都是采用低通滤波的方法消除噪声。
函数cvFilter2D对图像做卷积运算。
对图像进行线性滤波,支持替换方式操作。当核运算部份超出输入图像时,边界外面的像素值等于离它最近的图像像素值。
-Graph smoothing function of two-dimensional filtering of the image with different nuclear cvSmooth achieve a variety of methods. Generally, image smoothing is mainly in order to eliminate the noise. Common image noise additive noise, multiplicative noise and quantization noise. Since the image of energy is mainly concentrated in the low-frequency portion, while the frequency band where the noise in the high-frequency band, and therefore are usually using the method of the low-pass filtering to eliminate noise. Convolve the function cvFilter2D image. Linear image filtering, support the replacement operation. When the the nuclear operation part exceeds the input image, the pixel value outside the boundary is equal to the nearest image pixel value.
函数cvSmooth实现各种方法的图形平滑。
一般来说,图像平滑主要是为了消除噪声。图像的常见噪声主要有加性噪声、乘性噪声和量化噪声等。由于图像的能量主要集在低频部分,而噪声所在频段主要在高频段,因此通常都是采用低通滤波的方法消除噪声。
函数cvFilter2D对图像做卷积运算。
对图像进行线性滤波,支持替换方式操作。当核运算部份超出输入图像时,边界外面的像素值等于离它最近的图像像素值。
-Graph smoothing function of two-dimensional filtering of the image with different nuclear cvSmooth achieve a variety of methods. Generally, image smoothing is mainly in order to eliminate the noise. Common image noise additive noise, multiplicative noise and quantization noise. Since the image of energy is mainly concentrated in the low-frequency portion, while the frequency band where the noise in the high-frequency band, and therefore are usually using the method of the low-pass filtering to eliminate noise. Convolve the function cvFilter2D image. Linear image filtering, support the replacement operation. When the the nuclear operation part exceeds the input image, the pixel value outside the boundary is equal to the nearest image pixel value.
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