digital image processing elements of visual perception
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Digital Image ProcessingDigital Image Processing
Elements of Visual PerceptionElements of Visual Perception
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Structure of the human eye
Image formation in the human eye
Brightness adaptation and discrimination
OutlineOutline
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Structure of the human eyeStructure of the human eye
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
The cornea and sclera outer cover
The choroidCiliary body
Iris diaphragm
Lens
The retina (two kinds of receptors)Cones vision (photopic/bright-light vision) : centered at fovea, highly sensitive to color
Rods (scotopic/dim-light vision) : general view
Blind spot
Structure of the human eyeStructure of the human eye
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Flexible lens: the principle difference from an ordinary optical lens.
Controlled by the tension in the fibers of the ciliary body
To focus on distant objects – flattened
To focus on objects near eye – thicker
Near-sighted and far-sighted
Image formation in the human eyeImage formation in the human eye
Digital Image ProcessingDigital Image Processing
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Image formation in the eyeImage formation in the eye
Light receptor
radiant energy
electrical impulses
Brain
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Elements of Visual PerceptionElements of Visual Perception
Dynamic range of human visual system: 10-6~104 mL (millilambert)
Can not accomplish this range simultaneously
The current sensitivity level of the visual system is called brightness adaptation level
Brightness adaptationBrightness adaptation
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Brightness adaptationBrightness adaptation
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Weber ratio (the experiment) :
I: the background illumination
: the increment of illumination
Small Weber ratio indicates good discrimination
Larger Weber ratio indicates poor discrimination
Brightness discriminationBrightness discrimination
IIC /
CI
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Brightness discriminationBrightness discrimination
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
The perceived brightness is not a simple function of intensity
Mach band pattern
Simultaneous contrast
Optical illusion
Psycho-visual effectsPsycho-visual effects
Digital Image ProcessingDigital Image Processing
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Psychovisual effectsPsychovisual effects
The perceived brightness is not a simple function of intensity
Mach band pattern
Simultaneous contrast
And more… (see link)
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Mach band patternMach band pattern
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Simultaneous contrastSimultaneous contrast
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Elements of Visual PerceptionElements of Visual Perception
Optical illusionOptical illusion
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Optical illusionOptical illusion
Digital Image ProcessingDigital Image Processing
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Elements of Visual PerceptionElements of Visual Perception
Optical illusionOptical illusion
Digital Image ProcessingDigital Image Processing
Sampling, Quantization and Other Simple Sampling, Quantization and Other Simple OperationsOperations
Dr. Jiajun Wang
School of Electronics & Information Engineering
Soochow University
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Image formation model
Uniform sampling
Uniform quantization
Digital image representation
Relationships between pixels
Arithmetic operations
Logical operations
OutlineOutline
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization and Other Simple Sampling, Quantization and Other Simple OperationsOperations
0 ,f x y
,f x y
,i x y
may be characterized by two components :
Illumination: Reflectance: ,r x y
, , ,f x y i x y r x y
0 ,i x y 0 , 1r x y
Monochrome image
Typical values of the illumination and reflectance:
Illumination: sun on earth: 90,000 lm/m2 on a sunny day; 10,000 lm/m2 on a cloud day; moon on clear evening: 0.1 lm/m2; in a commercial office is about 1000 lm/m2
Reflectance: 0.01 for black velvet, 0.65 for stainless steel, 0.80 for flat-white wall paint, 0.90 for silver-plated metal, and 0.93 for snow
Image Formation ModelImage Formation Model
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Sampling
digitalized in spatial domain
Quantization
digitalized in amplitude
Uniform sampling and quantizationUniform sampling and quantization
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Uniform sampling and quantizationUniform sampling and quantization
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Digital image representationDigital image representation
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Spatial resolution : the more pixels in a fixed range, the higher the resolution
Gray-level resolution : the more bits, the higher the resolution
Image resolutionImage resolution
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Both applied to digital image
Zooming
Creation of new pixel locations
Assignment of gray levels to those new locations
Pixel replication, when increasing the size of an image an integer times
Nearest neighbor interpolation
Bilinear interpolation
Bicubic interpolation
Shrinking
Image zooming and shrinkingImage zooming and shrinking
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Bilinear InterpolationBilinear Interpolation
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Neighbors of a pixel
4-neighbors
diagonal-neighbors
8-neighbors
Adjacency
4-adjacency
8-adjacency
m-adjacency
Relationships between pixelsRelationships between pixels
(i-1,j-1)
(i-1,j)(i-
1,j+1)
(i,j-1) (i,j)(i,j+1
)
(i+1,j-1)
(i+1,j)
(i+1,j+1)
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
m-adjacency
Relationships between pixelsRelationships between pixels
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Path: 4, 8, and m-paths
A sequence of distinct pixels from pixel p to q.
Connectivity
Connect set: only has one connected component.
Region
Region is a connected set.
Boundary
The set of pixels in the region which has one or more neighbors that are not in the region.
Relationships between pixelsRelationships between pixels
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
Addition
Subtraction
Multiplication
Division
Arithmetic operationsArithmetic operations
Digital Image ProcessingDigital Image Processing
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Sampling, Quantization, and OperationsSampling, Quantization, and Operations
AND
OR
Complement (NOT)
XOR
Logical operationsLogical operations