Visual perception

1. Digital Image Processing
Elements of Visual Perception

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Elements of Visual Perception
Structure of the human eye
Image formation in the human eye
Brightness adaptation and discrimination
Outline

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Elements of Visual Perception
The cornea and sclera outer cover
The choroid
Ciliary 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 eye

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Elements of Visual Perception
Structure of the human eye

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Elements of Visual Perception
Structure of the human eye

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Elements 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 eye

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Elements of Visual Perception
Image formation in the human eye
Light
Receptor Brain
Radiant
Energy

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Elements of Visual Perception
Dynamic range of human visual system: 10-6~104 mL
(millilambert)
Can not accomplish this range simultaneously
It changes its sensitivity to operate over this entire range
simultaneously.
The current sensitivity level of the visual system is called
brightness adaptation level
Brightness adaptation

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Elements of Visual Perception
Brightness adaptation

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Elements 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 discrimination
I
IC /

C
I


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Elements of Visual Perception
Brightness discrimination

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Elements of Visual Perception
The perceived brightness is not a simple function of
intensity
Mach band pattern
Simultaneous contrast
Optical illusion
Psycho-visual effects

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Elements of Visual Perception
Mach band pattern

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Elements of Visual Perception
Simultaneous contrast

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Elements of Visual Perception
Optical illusion

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Elements of Visual Perception
Optical illusion

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Elements of Visual Perception
Optical illusion

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Sampling, Quantization and Other Simple
Operations

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Sampling, Quantization, and Operations
Image formation model
Uniform sampling
Uniform quantization
Digital image representation
Relationships between pixels
Arithmetic operations
Logical operations
Outline

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Sampling, Quantization and Other Simple
Operations
 
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 , 1
r 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 Model

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Sampling, Quantization, and Operations
Sampling
digitalized in
spatial domain
Quantization
digitalized in
amplitude
Uniform sampling and quantization

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Sampling, Quantization, and Operations
Uniform sampling and quantization

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Sampling, Quantization, and Operations
Digital image representation

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Sampling, 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 resolution

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Sampling, 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 shrinking

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Sampling, Quantization, and Operations
Bilinear Interpolation

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Sampling, Quantization, and Operations
Neighbors of a pixel
4-neighbors
diagonal-neighbors
8-neighbors
Adjacency
4-adjacency
8-adjacency
m-adjacency
Relationships 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 Operations
m-adjacency
Relationships between pixels

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Sampling, 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 pixels

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Sampling, Quantization, and Operations
Addition
Subtraction
Multiplication
Division
Arithmetic operations

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Sampling, Quantization, and Operations
AND
OR
Complement (NOT)
XOR
Logical operations