1. Lecture 2 Digital Image Fundamentals
Machine Vision
R. Ebrahimpour, 2008

2. Characteristics of HVS

3. Optical Illusions

4. Image sensing and acquisition

5. Three principle sensor arrangements:
1. Single imaging sensor
2. Line sensor
3. Array sensor

7. Image Sampling and Quantization

9. Representing Digital Images

10. The number of gray levels typically is an integer power of 2
L = 2^ k
.Number of bits required to store a digitized image
b = M x N x k

11. Project # 1 – part1

13. Zooming and Shrinkage
Zooming: increasing the resolution (size) of an image
Shrinkage: decreasing the resolution of an image
Example of zooming: we have an image of 500x500 pixels
and we want to enlarge it to 750x750
Zooming has two steps: creation of new pixel locations and the assignment of gray levels to those locations.
A simple way of zooming which works for increasing the size of an image by integer numbers is pixel replication.
Gray level of each pixel in the enlarged image is set to the gray-level of its nearest pixel in the original image

14. Interpolation of Data
Given a function at 4 points, how to “guess” values at other points?
x1, x2, x3, x4 are original points
X’i are new points
Guessing at the function values within the known range is called interpolation.
Interpolation has great significance in general image/video processing.

15. Interpolation: Nearest Neighbor
1-D
We assign f (xi’ )=f (xj)
xj is the original point closest to xi’
The original function values
The interpolated values
2-D x’ y’
Original point
Interpolated
point
setting the pixel value on interpolated point to the
pixel of closet image point

16. Project # 1- part2

17. Shrinkage Shrinkage by an integer number can be done by deleting some
of the rows and columns of the image
• Shrinkage by an noninteger factor can be done as the inverse
of zooming