image processing presentation
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Image processing GongalezTRANSCRIPT
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Image Processing
Ref: Digital image processing ,Gonzalez & Woods
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Components of an Image Processing System:
Ref: Digital image processing ,Gonzalez & Woods
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Image sensing
1. a physical device that is sensitive to the energy radiated by the object.
2. a digitizer
Technologies used1. Photo chemical, eg: photographic film 2. Photo electronic
The devices used 1. Still camera2. TV camera3. X ray scanner4. Radar5. Magnetic resonance imaging (MRI) system.
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Digitizer:
Ref: Digital image processing ,Gonzalez & Woods
Commonly used digitizers
1. Microdensitometer and
2. flying spot scanner.
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Digital storage:
Ref: Digital image processing ,Gonzalez & Woods
categorized as(1) short-term storage for use during processing, eg: frame buffers.(2) on-line storage for relatively fast re-call, and (3) archival storage, characterized by infrequent access.
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Image displays:
Ref: Digital image processing ,Gonzalez & Woods
Principal display devices are 1. printers, 2.TV monitor, 3. CRTs
Hardcopy:
laser printers, film cameras, heat-sensitive devices, inkjet units, and digital units, such as optical and CD-ROM disks, paper etc.
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Structure of the Human Eye
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Image Formation
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Sampling and Quantization
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Sampling and Quantization
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Spatial and Gray-Level Resolution:
Spatial Resolution: is the smallest discernible detail in an image.Gray—level resolution: refers to the smallest discernible change in gray level .-subjective process.
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Aliasing and Moiré Patterns:
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Zooming and Shrinking Digital Images:
Zooming 1. creation of new pixel locations2. assignment of gray levels to those new locations.
1.Nearest neighbor interpolation2. Pixel replication3. Bilinear interpolation
v(x', y') = ax' + by' + cx'y' + d a= f (1, 0)- f (0, 0)b= f (0, 1)- f (0, 0)c= f (0, 0)-f (1, 0)- f (0, 1)+ f (1, 1)d= f (0, 0)
Image shrinking
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2D bilenear interpolation
Original Before After No Interpolation
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Basic Point Processing
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Log
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Power-law transformations
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Gamma Correction
Gamma Measuring Applet: http://www.cs.berkeley.edu/~efros/java/gamma/gamma.html
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Image Enhancement
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Contrast Streching
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Histogram Equalization
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Periodic noise
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Mean and variance of the gray levels in image strips
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Wrong sign for Q
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Max and Min filter
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Alpha trimmed mean filter with d=5
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Adaptive noise reduction filtering
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What is an image?
We can think of an image as a function, f, from R2 to R:• f( x, y ) gives the intensity at position ( x, y )
• Realistically, we expect the image only to be defined over a rectangle, with a finite range:
– f: [a,b]x[c,d] [0,1]
A color image is just three functions pasted together. We can write this as a “vector-valued” function:
( , )
( , ) ( , )
( , )
r x y
f x y g x y
b x y
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Images as functions
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What is a digital image?
We usually operate on digital (discrete) images:• Sample the 2D space on a regular grid• Quantize each sample (round to nearest integer)
If our samples are apart, we can write this as:
f[i ,j] = Quantize{ f(i , j ) }
The image can now be represented as a matrix of integer values
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Image processing
An image processing operation typically defines a new image g in terms of an existing image f.
We can transform either the range of f.
Or the domain of f:
What kinds of operations can each perform?
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Point Processing
The simplest kind of range transformations are these independent of position x,y:
g = t(f)
This is called point processing.
What can they do?
What’s the form of t?
Important: every pixel for himself – spatial information completely lost!
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Image Histograms
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Cumulative Histograms
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Histogram Matching
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Match-histogram code
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Neighborhood Processing (filtering)
Q: What happens if I reshuffle all pixels within the image?
A: It’s histogram won’t change. No point processing will be affected…
Need spatial information to capture this.
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Programming Assignment #1
Easy stuff to get you started with Matlab• James will hold tutorial this week
Distance Functions• SSD• Normalized Correlation
Bells and Whistles• Point Processing (color?)• Neighborhood Processing• Using your data (3 copies!)• Using your data (other images)