Smoothing filters are also called low-pass filters because they let low frequency components pass and reduce the high frequency components.
The impulse response of a normal low-pass filter implies that all the coefficients of the mask should be positive. Low-pass filtering in effect blurs the image and removes speckles of high frequent noise. Larger masks will result in more blurring effect. To avoid a general amplification or damping of the data the sum of the filter coefficients should be 1.0.
Different types of smoothing are available:
In practice the low-pass filter can be used for creating high pass filters by subtracting the filtered result from the original image or by some other combination of the input image and the filtered result as described in the. "Unsharp Masking" section.