This document discusses different types of spatial filters that can be applied to images, including low-pass, high-pass, average, and median filters. Spatial filters work by applying a filter mask over an image and calculating new pixel values based on the neighborhood defined by the mask. Low-pass filters preserve low frequencies and are used for smoothing and blurring to reduce noise or small details. High-pass filters preserve high frequencies and are used to highlight edges and detail. Average filters reduce irrelevant detail through normalization, while median filters are effective for reducing salt-and-pepper noise with less blurring than linear filters.

1. Spatial Operation
Let’s
Discuss !!
-Averaging
-Median
-Filtering Spatial Low pass
-Filtering Spatial High pass

2. INTRODUCTION TO FILTERS
Filter:
Filter is a process that removes some unwanted components or
Small details in a image.
Types of Filters :
• Spatial Domain Filters
• Frequency Domain Filters

3. Spatial Domain Filters
The spatial filter is just moving the filter mask(neighborhood) from point to point in
an image. The filter mask may be 3*3 mask or 5*5 mask or to be 7*7 mask.
Example
3*3 mask in a 5*5 image
Filters are classified as:
 Low-pass (i.e preserve low frequencies)
 High-pass (i.e preserve high frequencies)
 Band-pass (i.e preserve frequencies within a band)
 Band-reject (i.e reject frequencies within a band)
Operation:-A filter image is generated as the center of the mask moves to every pixel in the input image.

4. Smoothing Filters (low-pass)
 Smoothing filters are used for blurring and for noise reduction.
 Blurring is used as preprocessing such as removal of small details
from image.
 Noise reduction is blurring with linear(output is a weighted sum of
the input pixels) or non linear filter.
 The elements of the mask must be positive.
 Sum of the mask elements is 1 (after normalization).

5. Sharpening Filters (high-pass)
 The sharpening spatial is to highlight the transactions in intensity.
 There are many application, such as medical images,military
systems are used this sharpening technique.
 The elements of the mask contain both positive and negative
weights.
 Sum of the mask elements is 0.

6. Average Filter
 A major use of averaging filter is in the reduction of “irrelevant”
detail in an image.
 Also known as low pass filter.
 M*N mask would have a normalizing constant equal to 1/M*N.

7. Median Filter
o Median filters used for noise-reduction with less blurring than linear smoothing filters of similar size.
o Median filters are particularly effective in the presence of impulse noise also called salt-and-pepper noise
because of its appearance as white and black dots superimposed on an image.