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Digital Image Processing Chapter 2: Digital Image Fundamentals
38

Image Processing

Jan 18, 2016

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Page 1: Image Processing

Digital Image Processing

Chapter 2: Digital Image Fundamentals

Page 2: Image Processing

Elements of Visual Perception

Structure of the human eye

Page 3: Image Processing

Rods and cones in the retina

Page 4: Image Processing

Image formation in the eye

Page 5: Image Processing

Brightness adaptation and discrimination

Page 6: Image Processing

Brightness discrimination

Page 7: Image Processing

Weber ratio

Page 8: Image Processing

Perceived brightness

Page 9: Image Processing

Simultaneous contrast

Page 10: Image Processing

Optical illusion

Page 11: Image Processing

Light and the Electromagnetic Spectrum

Page 12: Image Processing

Wavelength

c

hE

Page 13: Image Processing

Image Sensing and Acquisition

Page 14: Image Processing

Image acquisition using a single sensor

Page 15: Image Processing

Using sensor strips

Page 16: Image Processing

A simple image formation model

Page 17: Image Processing

Illumination and reflectance Illumination and transmissivity

),(),(),( yxryxiyxf

Page 18: Image Processing

Image Sampling and Quantization

Page 19: Image Processing

Sampling and quantization

Page 20: Image Processing

Representing digital images

Page 21: Image Processing

Number of storage bits

Page 22: Image Processing

Spatial and gray-level resolution

Page 23: Image Processing

Subsampled and resampled

Page 24: Image Processing

Varying the number of gray levels

Page 25: Image Processing

Varying the number of gray levels

Page 26: Image Processing

N and k in different-details images

Page 27: Image Processing

Isopreference

Page 28: Image Processing

Moire pattern

Page 29: Image Processing

Zooming and shrinking

Page 30: Image Processing

Some Basic Relationships Between Pixels

Neighbors of a pixel : 4-neighbors of p

, , ,

: four diagonal neighbors of p , , ,

: 8-neighbors of p and

)(4 pN

),1( yx )1,( yx),1( yx )1,( yx

)1,1( yx )1,1( yx)1,1( yx

)1,1( yx

)( pND

)(8 pN)(4 pN )( pND

Page 31: Image Processing

Adjacency : The set of gray-level values used to

define adjacency 4-adjacency: Two pixels p and q with

values from V are 4-adjacency if q is in the set

8-adjacency: Two pixels p and q with values from V are 8-adjacency if q is in the set

V

)(4 pN

)(8 pN

Page 32: Image Processing

m-adjacency (mixed adjacency): Two pixels p and q with values from V are m-adjacency if

q is in , or q is in and the set has

no pixels whose values are from V

)(4 pN)( pND )()( 44 qNpN

Page 33: Image Processing

Subset adjacency S1 and S2 are adjacent if some pixel in

S1 is adjacent to some pixel in S2 Path

A path from p with coordinates to pixel q with coordinates is a sequence of distinct pixels with coordinates

, ,…, where = , = ,

and pixels and are adjacent

),( yx),( ts

),( 00 yx ),( 11 yx ),( nn yx),( 00 yx ),( yx ),( nn yx ),( ts

),( ii yx ),( 11 ii yx

Page 34: Image Processing

Region We call R a region of the image if R is a

connected set Boundary

The boundary of a region R is the set of pixels in the region that have one or more neighbors that are not in R

Edge Pixels with derivative values that

exceed a preset threshold

Page 35: Image Processing

Distance measures Euclidean distance

City-block distance

Chessboard distance

2

122 ])()[(),( tysxqpDe

|)(||)(|),(4 tysxqpD

|))(||,)(max(|),(8 tysxqpD

Page 36: Image Processing

mD distance: The shortest m-path between the points

Linear operation H is said to be a linear operator if, for

any two images f and g and any two scalars a and b,

)()()( gbHfaHbgafH

Page 37: Image Processing

Example

Zooming and Shrinking Images by Pixel Replication

(a) Write a computer program capable of zooming and shrinking an image by pixel replication. Assume that the desired zoom/shrink factors are integers. You may ignore aliasing effects. You will need to download Fig. 2.19(a).

(b) Download Fig. 2.19 (a) and use your program to shrink the image from 1024 x 1024 to 256 x 256 pixels.

(c) Use your program to zoom the image in (b) back to 1024 x 1024. Explain the reasons for their differences.

Page 38: Image Processing

http://home.kimo.com.tw/abc9250/BMP_FILE.htm

Fig2.19(a).bmp subsample.c resample.c