文档介绍：Some of Basic Spatial Filtering
Spacial average filter
A spatial average filter in which all coefficients are equal is sometimes called a box filter. If not, it yields a so-called weighted average filter, indicating that pixels are multiplied by different coefficients, thus giving more imporatance (weight) to some pixels at the expense of others.
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
Median filter
Median filters are partically effective in the presence of impulse noise, also called salt-pepper noise because its apperance as white and black dots superimposed on images.
Max filter
Max filters are also called 100th percentile filters that are useful in finding the brightest points in an image. They can reduce pepper noise.
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
Min filter
Min filters are the 0th percentile filters that are useful for finding the lowest point in an image. They can reduce salt noise.
Mid-point filter
Mid-point filters are fit for noise like Gaussian and uniform noise.
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
Adaptive median filter
The adaptive median filtering algorithm works in two levels: Level A and Level B.
Level A:
If A1>0 & A2<0
go to level B
Else
Increase the window size
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
If window size >
Output
Else
Repeat Level A
Level B:
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
If B1>0 & B2<0
Output
Else
Output
= minimum gray level value in
= maximum gray level value in
= median gray level value in
= gray level coordinates (x,y)
= maximum allowed size of
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
Chapter 2
Image Pre-Processing in the
Spatial and Frequent Domain
Some of Basic Frequency Filtering
Filtering in the frequency domain is straightforward. It consists of the following steps:
Multiply t