数字图像处理(冈萨雷斯第三版)英文翻译PPT课件
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数字图像处理课件(冈萨雷斯第三版)
数字图像处理Digital Image Processing合肥工业大学理学院信息与计算科学系二零零九年1.1 从图象到图像工程1.1.1 图象和数字图象•什么是图象？图象(image)是泛指照片、动画等等形成视觉景象的事物。
图象与计算机图形学中的图形的区别是：计算机图形学是从建立数学模型到生成图形，而图象通常是指从外界产生的图形。
客观世界是三维空间，但一般图象是二维的。
二维图象在反映三维世界的过程中必然丢失了部分信息。
即使是记录下来的信息也可能有失真，甚至于难以识别物体。
因此，需要从图象中恢复和重建信息，分析和提取图象的数学模型，以至于形成人们对于图象记录下的事物有正确和深刻的认识。
这个过程就成为图象处理过程。
•为什么需要数字图象(digital image )？普通图象包含的信息量巨大，需要使用计算机对图象进行处理。
因此，需要把普通图象转变成计算机能处理的数字图象。
现在的数码相机可以直接地把视觉图象变成数字图象。
数字图象类似于光栅图形，由有限行和有限列组成。
每个基本单元叫做一个象素(pixel)。
三维图象的象素又叫做体素(voxel)。
通常的二维数字图像是一个矩型，可以用一个二维数组I(x,y) 来表示，其中x,y是二维空间中的某坐标系的坐标，I(x,y)表示图像在该点处的灰度值等性质。
彩色可以是红绿蓝三个单色的一定灰度值的合成。
一般来说，这些坐标和灰度值是实数，不仅依赖于坐标系的选取，而且依赖于灰度值的度量单位。
但是，数字计算机只可能表示有限字长的有限个数字。
所以必须把灰度值离散化。
简单地说，数字图象等同于一个整数值的有限矩阵。
数字图像是数字图像处理和分析的对象。
左边的图象是图象处理技术中常用来检验计算机算法的实际效果的标准图象。
这幅图象的名称是lenna。
它是由一组数字组成的。
原图象的宽和高都是256个象素，每象素有八位。
它在BMP格式下有约66K字节的大小。
数字图像处理-冈萨雷斯-课件(英文)Chapter04 频域图像增强
1
F (u ) R(u ) I (u )
2
2
Example of 1-D Fourier Transforms
Notice that the longer the time domain signal, The shorter its Fourier transform
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
g(x,y) -M
0
For an image of size NxM pixels, its 2-D DFT repeats itself every N points in xdirection and every M points in y-direction.
M
2M
-N 0 N 2N
We display only in this range
2-D FFT Shift is a MATLAB function: Shift the zero frequency of F(u,v) to the center of an image.
2D FFTSHIFT
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
2-D DFT Properties
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
F (u ) R(u ) I (u )
2
2
Example of 1-D Fourier Transforms
Notice that the longer the time domain signal, The shorter its Fourier transform
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
g(x,y) -M
0
For an image of size NxM pixels, its 2-D DFT repeats itself every N points in xdirection and every M points in y-direction.
M
2M
-N 0 N 2N
We display only in this range
2-D FFT Shift is a MATLAB function: Shift the zero frequency of F(u,v) to the center of an image.
2D FFTSHIFT
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
2-D DFT Properties
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
数字图像处理_冈萨雷斯_课件英文版Chapter09形态学图像处理
Extraction of Connected Components
X k X k 1 B A
where X0 = seed pixel p
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Example: Extraction of Connected Components X-ray image of bones
Thresholded image
Connected components
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
A B ((...((A B1 ) B2 )...) Bn )
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Example: Thinning
Duality Between Dilation and Erosion
ˆ ( A B) A B
c c
where c = complement
Proof:
( A B ) z B z A
c c
c c
z B z A z B z Ac ˆ A B
Dilation Operations
ˆ A A B z B z
= Empty set
数字图像处理-冈萨雷斯-课件(英文)Chapter03-空域图像增强
- Histogram matching To make histogram as the desire
Monotonically Increasing Function = Function that is only increasing or constant
Ds Dr
Smaller Dr yields wider Ds = increasing Contrast
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Gray Level Slicing
Contrast Stretching
Contrast means the difference between the brightest and darkest intensities
Before contrast enhancement
After
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Images in the spatial domain are pictures in the xy plane
where the word “distance” is meaningful.
Using the Fourier
transform, the word “distance” is lost but the word “frequency” becomes alive.
Image Negative
L-1 White
Monotonically Increasing Function = Function that is only increasing or constant
Ds Dr
Smaller Dr yields wider Ds = increasing Contrast
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Gray Level Slicing
Contrast Stretching
Contrast means the difference between the brightest and darkest intensities
Before contrast enhancement
After
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Images in the spatial domain are pictures in the xy plane
where the word “distance” is meaningful.
Using the Fourier
transform, the word “distance” is lost but the word “frequency” becomes alive.
Image Negative
L-1 White
数字图像处理-冈萨雷斯-课件(英文)Chapter11 表示与描述
Step 1. Mark pixels for deletion if the following conditions are true. a) 2 N ( p1 ) 6 (Apply to all border pixels) p9 p2 p3 b) T(p1) =1 p8 p1 p4 c) p2 p4 p6 0 p7 p6 p5 d) p4 p6 p8 0 Step 2. Delete marked pixels and go to Step 3. Step 3. Mark pixels for deletion if the following conditions are true. a) 2 N ( p1 ) 6 (Apply to all border pixels) b) T(p1) =1 c) p2 p4 p8 0 d) p2 p6 p8 0
0. Object boundary
3. Draw a polygon
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Distance-Versus-Angle Signatures Represent an 2-D object boundary in term of a 1-D function of radial distance with respect to q.
Turn Right OK! Turn Right OK! Turn Left NOK!
Convex Hull Algorithm (cont.)
For the lower side of a convex hull 7. Put the points pn and pn-1 in a list Llower w 8. For i = n-2 down to 1 9. Do append pi to Llower 10. While Llower contains more than 2 points in Llower do not make a right turn 11. Do delete the middle point of the 12. Remove the first and the last points fro 13. Append Llower to Lupper resulting in the lis 14. Return L
0. Object boundary
3. Draw a polygon
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Distance-Versus-Angle Signatures Represent an 2-D object boundary in term of a 1-D function of radial distance with respect to q.
Turn Right OK! Turn Right OK! Turn Left NOK!
Convex Hull Algorithm (cont.)
For the lower side of a convex hull 7. Put the points pn and pn-1 in a list Llower w 8. For i = n-2 down to 1 9. Do append pi to Llower 10. While Llower contains more than 2 points in Llower do not make a right turn 11. Do delete the middle point of the 12. Remove the first and the last points fro 13. Append Llower to Lupper resulting in the lis 14. Return L
数字图像处理(冈萨雷斯第三版)ppt课件
.
• 什么是图像工程？（广义的数字图像处理）
它是由图像处理、图像分析和图像理解三个系统所组 成。图像处理包括图像采集和从图像到图像的变换，以改 善主观的视觉效果和为图像分析和图像理解作初步的处理。 图像分析是从图像中取出感兴趣的数据，以描述图像中目 标的特点。图像理解是在图像分析的基础上研究各目标的 性质和相互关系，以得出图像内容的理解和对原场景的解 释。图像处理、图像分析和图像理解是处在从低到高的三 个不同的抽象程度上的过程。本课程着重于图像处理和分 析系统。
.
图像数据文件主要是用光栅形式,即图像是一些图像点 的集合，比较适合变化复杂的图像。它的主要缺点是缺少 对象和像素点之间的联系,且在伸缩图像的过程中图像会 改变。例如，常见的图象文件类型有bmp,jpg等等。图象 处理的程序必须考虑图象文件的格式，否则无法正确地打 开和保存图象文件。
pgm格式
美国的许多大学用pgm格式，避免使用压缩文件格式，对 初学者来说是很方便的。下面是一幅该格式的图象。
0x36 0x34 0x30 0x20 0x34
0x38 0x30 0x0A 表示640(SP)480(LF);
0x32 0x35 0x35 0x0A ………………………………… 表示255(LF) ………………………………… 0x27 0x27 …
. 表示23, 23,…(像素灰度值)
.
这幅图象文件的解码:
P5 # Imported from SUN image: LEGGO_HOUSE_1.0.intensity 640 480 255 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x26 0x27 0x27 0x27 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x26 0x27 0x26 0x27 0x28 0x27 0x27 0x26 0x27 0x27 0x27 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x28 0x28 0x27 0x28 0x29 0x28 0x27 0x28 0x28 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x28 0x27 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x29 0x29 0x29 0x28 0x28 0x28 0x28 ………………………………………………………………...
• 什么是图像工程？（广义的数字图像处理）
它是由图像处理、图像分析和图像理解三个系统所组 成。图像处理包括图像采集和从图像到图像的变换，以改 善主观的视觉效果和为图像分析和图像理解作初步的处理。 图像分析是从图像中取出感兴趣的数据，以描述图像中目 标的特点。图像理解是在图像分析的基础上研究各目标的 性质和相互关系，以得出图像内容的理解和对原场景的解 释。图像处理、图像分析和图像理解是处在从低到高的三 个不同的抽象程度上的过程。本课程着重于图像处理和分 析系统。
.
图像数据文件主要是用光栅形式,即图像是一些图像点 的集合，比较适合变化复杂的图像。它的主要缺点是缺少 对象和像素点之间的联系,且在伸缩图像的过程中图像会 改变。例如，常见的图象文件类型有bmp,jpg等等。图象 处理的程序必须考虑图象文件的格式，否则无法正确地打 开和保存图象文件。
pgm格式
美国的许多大学用pgm格式，避免使用压缩文件格式，对 初学者来说是很方便的。下面是一幅该格式的图象。
0x36 0x34 0x30 0x20 0x34
0x38 0x30 0x0A 表示640(SP)480(LF);
0x32 0x35 0x35 0x0A ………………………………… 表示255(LF) ………………………………… 0x27 0x27 …
. 表示23, 23,…(像素灰度值)
.
这幅图象文件的解码:
P5 # Imported from SUN image: LEGGO_HOUSE_1.0.intensity 640 480 255 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x26 0x27 0x27 0x27 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x26 0x27 0x26 0x27 0x28 0x27 0x27 0x26 0x27 0x27 0x27 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x28 0x28 0x27 0x28 0x29 0x28 0x27 0x28 0x28 0x28 0x27 0x27 0x27 0x27 0x27 0x27 0x27 0x28 0x27 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x28 0x29 0x29 0x29 0x28 0x28 0x28 0x28 ………………………………………………………………...
数字图像处理-冈萨雷斯-课件(英文)Chapter03-空域图像增强
Image Negative
L-1 White
s L 1 r
Original digital mammogram
Output intensity
Black
0 Black
Input intensity
L-1 White
L = the number of gray levels
ห้องสมุดไป่ตู้
Negative digital
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Image Enhancement Example
Original image
Enhanced image using Gamma correction
mammogram
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Log Transformations
s c log(r 1)
Types of Image Enhancement in the Spatial Domain
- Single pixel methods - Gray level transformations Example - Historgram equalization - Contrast stretching - Arithmetic/logic operations Examples - Image subtraction - Image averaging
数字图像处理-冈萨雷斯-(英文)Chapter11 表示与描述PPT精选文档
an image in other forms that are more suitable than the image itself.
Benefits: - Easier to understand - Require fewer memory, faster to be processed - More “ready to be used”
7
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Distance-Versus-Angle Signatures Represent an 2-D object boundary in term of a 1-D function
8-directional chain code
(Images from Rafael C.
Gonzalez a3nd Richard E.
Wood, Digital Image Processing, 2nd Edition.
Examples of Chain Codes
Object boundary (resampling)
1
difference - a chain code: 10103322
01
1
- The first difference = 3133030
2
0 02
2
- Treating a chain code as a
03
3
circular sequence, we get
ቤተ መጻሕፍቲ ባይዱ
3
23
1
20
Benefits: - Easier to understand - Require fewer memory, faster to be processed - More “ready to be used”
7
(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Distance-Versus-Angle Signatures Represent an 2-D object boundary in term of a 1-D function
8-directional chain code
(Images from Rafael C.
Gonzalez a3nd Richard E.
Wood, Digital Image Processing, 2nd Edition.
Examples of Chain Codes
Object boundary (resampling)
1
difference - a chain code: 10103322
01
1
- The first difference = 3133030
2
0 02
2
- Treating a chain code as a
03
3
circular sequence, we get
ቤተ መጻሕፍቲ ባይዱ
3
23
1
20
数字图像处理冈萨雷斯英文Chapter空域图像增强讲课文档
where f(x,y) is an original image, g(x,y) is an output and
T[ ] is a function defined in the area around (x,y)
Note: T[ ] may have one input as a pixel value at (x,y) only or multiple inputs as pixels in neighbors of (x,y) depending in
Bit 2
第十八页，共75页。
Bit 1 (Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Histogram
Histogram = Graph of population frequencies
Power-Law Transformations : Gamma Correction Application
MRI Image after
Gamma Correction
第十三页，共75页。
(Images from Rafael C. Gonzalez and Richard E.
Wood, Digital Image Processing, 2nd Edition.
mammogram
(Images from Rafael C. Gonzalez and Richard E.
Wood, Digital Image Processing, 2nd Edition.
Log Transformations
sclog(r1)
T[ ] is a function defined in the area around (x,y)
Note: T[ ] may have one input as a pixel value at (x,y) only or multiple inputs as pixels in neighbors of (x,y) depending in
Bit 2
第十八页，共75页。
Bit 1 (Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.
Histogram
Histogram = Graph of population frequencies
Power-Law Transformations : Gamma Correction Application
MRI Image after
Gamma Correction
第十三页，共75页。
(Images from Rafael C. Gonzalez and Richard E.
Wood, Digital Image Processing, 2nd Edition.
mammogram
(Images from Rafael C. Gonzalez and Richard E.
Wood, Digital Image Processing, 2nd Edition.
Log Transformations
sclog(r1)
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necessary to transform ordinary images into digital images that the
computer can process. Today's digital cameras can directly convert
visual images into digital images. A digitห้องสมุดไป่ตู้l image, similar to raster
Digital Image Processing
Tianjin University of Technology and Education School of Electronic Engineering
2017
-
1
Synopsis
The contents of the eight weeks are as follows: The first、second chapter is the introduction and the
The objective world is a three-dimensional space, but the general image is two-dimensional. Two dimensional images inevitably lose part of the information in the process of reflecting the threedimensional world. Even recorded information can be distorted and even difficult to recognize objects. Therefore, it is necessary to recover and reconstruct information from images, and to analyze and extract mathematical models of images so that people can have a correct and profound understanding of what is recorded in the image. This process becomes the process of image processing.
basic concept of image processing. The third, fourth chapter is space domain and frequency
domain transform The fifth, eighth chapter is image enhancement and
image restoration. The sixth chapter is image coding The seventh, ninth chapter is image segmentation and
morphology The tenth chapter, other
-
2
The first chapter is introduction
1.1 From image to image engineering
– Image and digital image – Image technology and image engineering – Related disciplines and fields.
1.2 Image processing and analysis
– Image processing and analysis system – Image acquisition, display, storage, communication, processing
and analysis module
-
3
Image understanding
Abstract degree image analysis Data quantity
graphics, consisting of finite rows and finite columns. Each basic unit
is called a pixel. The voxel of a three-dimensional image is also
called voxel. The two-dimensional digital image usually is a
rectangle, you can use a two-dimensional array of I (x, y) to said,
image processing
Image foundation
-
4
1.1 From image to image engineering
1.1.1 Image and digital image
• What is an image?
An image is a visual representation of pictures, animations, etc.. The difference between graphics and computer graphics is that computer graphics are from building mathematical models to generating graphics, and images usually refer to graphs generated from outside.
-
5
• Why do you need digital images?
Ordinary images contain enormous amounts of information and
require the use of computers to process images. Therefore, it is