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BBM 413
Fundamentals of
Image Processing
Erkut Erdem Dept. of Computer Engineering Hacettepe University
Point Operations
Histogram Processing
Today’s topics
- Point operations
- Histogram processing
Digital images
- Sample the 2D space on a regular grid
- Quantize each sample (round to nearest integer)
- Image thus represented as a matrix of integer values. Slide credit: K. Grauman, S. Seitz 2D 1D
Image Transformations
- g (x,y)= T [ f (x,y)] g (x,y): output image f (x,y): input image M: transformation function
- Point operations: operations on single pixels
- Spatial filtering: operations considering pixel neighborhoods
- Global methods: operations considering whole image
Image Transformations
- g (x,y)= M [ f (x,y)] g (x,y): output image f (x,y): input image M: transformation function
- Point operations: operations on single pixels
- Spatial filtering: operations considering pixel neighborhoods
- Global methods: operations considering whole image g ( x , y ) = M ({ f ( i , j ) |( i , j )Î N ( x , y )})
Point operations
- Smallest possible neighborhood is of size 1x
- Process each point independently of the others
- Output image g depends only on the value of f at a single point (x,y)
- Map each pixel’s value to a new value
- Transformation function T remaps the sample’s value: s = T(r) where
- r is the value at the point in question
- s is the new value in the processed result
- T is a intensity transformation function
Sample intensity transformation
functions
- Image negatives
- Log transformations
- Compresses the dynamic range of images
- Power-law
transformations
Sample intensity transformation
functions
- Image negatives
- Log transformations
- Compresses the dynamic range of images
- Power-law
transformations
Point Processing Examples
produces an image of higher contrast than the original by darkening the intensity levels below k and brightening intensities above k produces a binary (two-intensity level) image
Point Processing Examples
produces an image of higher contrast than the original by darkening the intensity levels below k and brightening intensities above k produces a binary (two-intensity level) image
Changing the image mean
Slide credit: Y. Hel-Or
Image Mean
v M(v) 255 255 M ( v ) = 255 - v Slide credit: Y. Hel-Or
Image Negative
Point Operations:
Contrast stretching and Thresholding
- Contrast stretching: produces an image of higher contrast than the original
- Thresholding: produces a binary (two-intensity level) image
Point Operations:
Contrast stretching and Thresholding
- Contrast stretching: produces an image of higher contrast than the original
- Thresholding: produces a binary (two-intensity level) image
Point Operations
- How we can process the image so that it has a better visual quality?
- Answer is contrast stretching!
Point Operations
- Let us devise an appropriate point operation.
- Shift all values so that the observable pixel range starts at 0.