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Filtering Images
• Creates new image• Each pixel is based on the corresponding pixel
and its neighbors in the old image• Filters can be used to clean images
“Noisy” Picture
Average Filter:Each pixel in new image will be the
average (mean) of a region of pixels in the
old image. Cleaned Picture
Median Filter:Each pixel in new image will be the
median of a region of pixels in the old
image.
Laplacian Filter
• Laplacian filter is a filter looking like this:• The Laplacian filter detects points (or
areas) that are different from their surrounding.
• Us humans see the world• Through Laplacian filter
The Problem of Scale
• The computer can easily fill in small gaps in the image to clean up noise.
• There are problems with larger gaps.
• Solution: Work on different scales.
Filter
Picture With Larger Bad Piece Just Filtering is Not Effective!
Gaussian Pyramids
• G0 = Original Image
• GN, N > 0 = Reduced Image
G0 G1 G2 …
Expand
Expand
Low DetailMuch Higher Detail
Much Higher Detail
Using Filters As Pyramids
• Filters can accomplish the same blurring as Gaussian pyramids.
• Gaussian filters create this blurring effect by emphasizing the corresponding pixel’s neighbors more than the corresponding pixel
Apply Large, Strong Gaussian Filter
Lower Detail
Apply Small, Weak Gaussian Filter
Approximations
• G0s of similar images = quite different
• GNs of similar images are closer than G0s
Find GNs with Large N
Very Slightly Similar Slightly More Similar
Image Completion
• Method for Image Completion– Repeat with N from a large number to 0
• Obtain a filtered version of GN, enlarged to the original size (Using filters or a Gaussian pyramid)
• Reintroduce the good pixels from the incomplete image
Incomplete Image Mask (Marks Valid Pixels) Complete Image
Another Example
• Can you see the Einstein in 100 random lines?
Incomplete Image Mask (Marks Valid Pixels) Complete Image
Limitations
• This method does not work as well on drawings because drawings can have more unpredictable changes in color.
Incomplete Image Mask (Marks Valid Pixels) Complete Image
Resizing Images
• Our task was making images smaller.• Why?• One reason is to transmit the image over the
internet faster.
But how do you resize an image?
• There a few methods to resize images and to reduce their number of pixels:
• The simplest reduce method is to use the ‘uniform grid’
Adaptive Sub-sampling
• To keep more pixels where details are finer
• Using Feature Detection to sample (take) more pixels near features
• Non-uniform grid