1' Image Enhancement Using Logic Operations

1
1. Image Enhancement Using Logic Operations
2
2. Image Enhancement Using Arithmetic Operation
Subtraction

• Equation g i, j f i, j b i, j
• Mostly used for background subtraction. b(x, y)
  is the background image.
• Need to consider/reduce noise.

3
Image Enhancement Using Arithmetic Operation
Average

• Equation g i, j (f1 i, j f2 i, j
  fk i, j )/k
• Goal reduce zero-mean additive noise
• Frequently used noise model Gaussian Noise
• Disadvantage blur caused by camera motion.

4
Image Enhancement Using Arithmetic Operation
Addition Example
5
3. Spatial Image Filters (Masks)

• Implement neighborhood operation mapping
  multiple original pixels to one output pixels.
• For computation purposes easy to compute.
• Different filters implement different image
  enhancement functions
• Smoothing filters
• Sharpen filters
• Etc.
• How to design filters? Fourier frequency analysis
  (next chapter)

6
Spatial Image Filters cont.
7
Spatial Image Filters cont.
8
3.1 Spatial Image Filters smoothing filter
results
Original image, smoothing filters of size 3, 5,
9, 15, 35
9
Spatial Image Filters smoothing filter results
10
3.2 Sharpen Image Filters
11
Sharpen Image Filters Laplacian
12
Sharpen Image Filters Laplacian
13
Sharpen Image Filters Laplacian
14
Sharpen Image Filters First derivatives
(gradient) masks
Roberts Cross Gradient
Sobel Filter
15
Sharpen Image Filters First derivatives
(gradient)
16
3.3 Combining Spatial Enhancement Methods
17
Combining Spatial Enhancement Methods (cont.)
18
3.4 Non-linear image filter

• Median filter
• Goal reduce salt-and-pepper noise