1. Image Processing Objectives To understand pixel based image processing
To use nested iteration
To implement a number of image processing algorithms
To understand passing functions as parameters

2. Color Color is continuous We perceive colors differently
Visible light is in the wavelengths of 370 and 730 nm ( and meters)
We perceive colors differently

3. Color Perception Human perception of light With three color sensors
Peaks at 425 nm (blue), 550 nm (green), and 660 nm (red)
Our brain figures out color by how much of each sensor is responding
Dogs and other simpler animals have two sensors
They do see color. Just less color

4. Luminance vs. Color Luminance is a measure of light intensity
Luminance allows us to perceive borders of things, motion, depth
Luminance perception is color blind.
Brightness is our perception of luminance
brightness is not the amount of light, but our perception of the amount of light.
We see blue as “darker” than red, even if same amount of light.
Much of our luminance perception is based on comparison to backgrounds, not raw values.
White’s illusion
Same gray luminance
Appears brighter in
black stripe
Different parts of the brain perceive color and luminance.

5. Digital Pictures Digitized as a bunch of dots (squares)
With enough dots, it looks continuous
Our eyes have limited resolution
Our background/depth acuity is particulary low
Each picture element is referred to as a pixel

6. Pixels Pixels are picture elements A picture is a matrix of pixels
Each pixel object “knows” its color
e.g. given a pixel, a Python function can get the color out of it.
It also “knows” where it is in its picture
e.g. given a pixel and a picture, a Python function can find out where the pixel is located in the picture
A picture is a matrix of pixels
With rows of pixels as arrays
With two dimensions: Width and Height
We need a two-dimensional array: a matrix

7. Digital Image Processing
Editing and manipulating digital images
A digital image is a collection of pixels
A pixel is the smallest amount of information available in a digital picture
Each pixel represents a single color
Pixels are organized in a grid

8. What is a Binary number ? What is a decimal number ?
Digits 0, 1, 2, …, 9
What does a decimal number 213 mean ?
Digit position has a weight associated with it
Binary ?
0,1
What is 1010 ?
Other number systems (bases) ?
12: month, foot/inch,
16: fluid oz 60

9. 3-bit Binary Number Binary Number System Base 2 Number
Base 10 Equivalent
000
001 1
010 2
011 3
100 4
101 5
110 6
111 7
Power
Positional Value 20 1 21 2 22 4 23 8 24 16 25 32 26 64 27
128

10. 4-bit Binary Hexadecimal Number
0000 1
0001 2
0010 3
0011 4
0100 5
0101 6
0110 7
0111 8
1000 9
1001 A 10
1010 B 11
1011 C 12
1100 D 13
1101 E 14
1110 F 15
1111
Hex
Decimal
Binary
Hexadecimal
Base 16 number representation
Use characters ‘0’ to ‘9’ and ‘A’ to ‘F’

11. 8-bit Binary Number Byte = 8 bits Binary 000000002 to 111111112
Decimal: 010 to
Hexadecimal to FF16

12. Color Encoding
Each pixel encodes color at that position in the picture
Most common for computers
RGB (Red, Green, Blue)
Each does appear as a separate dot on most devices, but our eye blends them.
In most computer-based models of RGB, a single byte (8 bits) is used for each
lEach color component has a value between 0 and 255
Total RGB color is 24 bits

13. Encoding RGB Colors go from (0,0,0) to (255,255,255)
If all components have the same values -> grayscale
(50,50,50) at (2,2)
(0,0,0) at (1,2) is black
(255,255,255) is white
Colors are represented in 24 bits
That is 16,777,216 (224) possible colors
Our eyes can discern millions of colors -> close
But, we don’t get 16 million colors from computer monitors