digital image processing elements of visual perception

Digital Image ProcessingDigital Image Processing

Elements of Visual PerceptionElements of Visual Perception


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Structure of the human eye

Image formation in the human eye

Brightness adaptation and discrimination

OutlineOutline


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Structure of the human eyeStructure of the human eye


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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


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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


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Image formation in the eyeImage formation in the eye

Light receptor

radiant energy

electrical impulses

Brain


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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


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Brightness adaptationBrightness adaptation


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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


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Brightness discriminationBrightness discrimination


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The perceived brightness is not a simple function of intensity

Mach band pattern

Simultaneous contrast

Optical illusion

Psycho-visual effectsPsycho-visual effects


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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)


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Mach band patternMach band pattern


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Simultaneous contrastSimultaneous contrast


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Optical illusionOptical illusion


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Sampling, Quantization and Other Simple Sampling, Quantization and Other Simple OperationsOperations

Dr. Jiajun Wang

School of Electronics & Information Engineering

Soochow University


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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


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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


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Sampling

digitalized in spatial domain

Quantization

digitalized in amplitude

Uniform sampling and quantizationUniform sampling and quantization


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Uniform sampling and quantizationUniform sampling and quantization


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Digital image representationDigital image representation


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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


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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


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Bilinear InterpolationBilinear Interpolation


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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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m-adjacency



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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.



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Addition

Subtraction

Multiplication

Division

Arithmetic operationsArithmetic operations


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AND

OR

Complement (NOT)

XOR

Logical operationsLogical operations

digital image processing elements of visual perception

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