2infinity-project.org
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Outline
• How Can We Use Digital Images?
• A Digital Image is a Matrix
• Manipulating Images
• Improving Images for Robot Eyes
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4.1 How Can We Use Digital Images?
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The Power of Digital Images
• It is easier and easier to acquire or make digital imagesDigital cameras and scanners
• Chief advantage over analog (e.g. film) images: Easy to change
• How might we change images?
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Image Softening and Blurring
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Image Sharpening
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Finding Edges in Images
• Edges in images usually define solid objects in our 3D world
• Finding edges is a first step to navigation and manipulation
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Subtracting Images
•Image subtraction is a simple way to find differences between two images
•Useful for security, recognition, and navigation applications
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Image Segmentation
• Segmentation: Dividing images into regions
• Applications Identifying
foreground vs. background
Finding objects using only one image
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4.2 A Digital Image Is a Matrix
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Digital Images are Matrices
• Matrix: An array of numbers
A =
101134
5610
751214 3 rows and 4 columns
• Elements: A(i,j) , i and j are integers
Examples: A(2,3) = 6,A(1,4) = 7, A(3,4) = 10
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Classes of Image Manipulation
1. Mapping: Pixel-by-pixel operations2. Arithmetic Combination of Two Images:
e.g. addition, multiplication3. Filtering: Operations on groups of pixels
in an image (neighborhood operation)Fact: Almost all applications are made up of
simple combinations of these manipulations
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Image Mapping
• All of the form B(i,j) = {function of
A(i,j)}
where B(i,j) is the output image
• Many familiar effects:Brightness, Contrast, Negative,
Thresholding, Gamma Correction
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k = -50
k = 50
Brightness Mapping
B(i,j) = A(i,j) + kk = constant
(expressed as a table)
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Example: Brightness Mapping
Original 24-bit image
Each color increased
by 60
Each color decreased
by 60
Green and blue +60, red -60
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Contrast Mapping
• Formula: B(i,j) = s • A(i,j) If s > 1, contrast is increased If s < 1, contrast is decreased
• Need to quantize after multiplying, as s • A(i,j) may not be an integer
• Aside: This setting is found on most TV sets
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Contrast Mapping (cont.)
s > 1
s < 1
s > 1 and k < 0
s < 1 and k > 0
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Example: Contrast and Brightness
• Formula: B(i,j) = s • A(i,j) + k
• This is easy to do!
Higher contrast
Higher contrast
with lower
brightness
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Example: Contrast and Brightness
• Given the 4-bit grayscale image
A =
101134
5610
751214
• Compute the image with a contrast of 1.5 and a
brightness of 2
20infinity-project.org
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Solution: Contrast and Brightness
• Answer: B(i,j) = 1.5•A(i,j) + 2
B = 151578
101142
13101515 Quantization causes values such as 9.5 and 3.5 to be rounded up
Image is clipped at 15
(Why?)
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Infinity Project Experiment – 4.1
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Brightness and Contrast Grayscale
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Brightness and Contrast Color Image
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Brightness and Contrast Color Camera
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Brightness and Contrast Cascade
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