Digital Image Processing

Digital Image Processing
Introduction to myself My name is Zou Beiji Education Background 1978 – Zhejiang University B.D Computer Software. 1982 – Qinghua University M.D Computer Application. 1997 – Hunan University Ph.D Control Theory and Engineering Research Experience 2002 – 2003 Qinghua University Post Doctor 2003 – Griffith University, Australia. Visiting Scholar. 2019/5/22 Digital Image Processing

Service 1984 – Hunan University, As a teacher, professor. 2004 – now Central South University, Professor My Research Field Computer Graphics, Digital Image Processing, Multimedia Tech. Contact Information Add. Tel. No , My office located. Computer Building No. 410 2019/5/22 Digital Image Processing

Teaching Schedule Lecture 1 Introduction Lecture 2 Image Enhancement in the Spatial Domain Lecture 3 Image Enhancement in the Frequency Domain Lecture 4 Image Restoration Lecture 5 Color Image Processing Lecture 6 Image Compression All students (M.S and Ph.D) have classes together here from the 10th week (this week) to the 15th week, I will talk one lecture each Monday morning. After finishing all contents above, I will have different arrangements and assessments for M.S students and Ph.D students. 2019/5/22 Digital Image Processing

Lecture 1: Introduction
Digital Image Processing Lecture 1: Introduction 2019/5/22 Digital Image Processing

Why do we need to study DIP? Interest in digital image processing methods stems from two aspects: Improve images for human interpretation; Process images, include storage,transmission and representation for autonomous machine perception. 2019/5/22 Digital Image Processing

1.1 What is a digital image ? . An image may be defined a two-dimension function f(x,y) (x,y) ---- coordinate for a point in a plane. f intensity or gray or color in the position (x,y) . Digital image digitize to the function f and coordinates (x,y) let them become discrete values. Usually f,x and y are all finite values. . Pixel a point in a digital image is called pixel. . Digital Image Processing regarded as a discipline from an image to another. 2019/5/22 Digital Image Processing

1.2 The Origins of Digital image Processing . The first application was in newspaper industry in 1920s 2019/5/22 Digital Image Processing

They were not real image processing, only image encoding and printing and some improvements. In 1960s, computer and its programming were brought into, the true image processing began. Two important events push forward digital image processing. Space Program --- First Moon Probe ( America, in 1964); In medicine --- CAT or CT (Computer Axial Tomography early 1970s) Using X-rays generates image. 2019/5/22 Digital Image Processing

1.3 Objectives of digital image processing 1.Improve qualities of images so that human can interpret them better. Such as enhancement, restoration and so on. 2.Process pictures and extract some information from them for machine perception. Such as image analysis, image recognition and so on. 2019/5/22 Digital Image Processing

1.4 Three level-processes for a digital image .Low-level processes:reduce noises,contrast enhancement and so on, from an image to another, improve the image quality; .Mid-level processes: extract some attributes from an image, segment an image, extract object contour in an image .High-level processes: recognize objects in an image for analysis There is no obvious boundary between digital image processing and computer vision. Computer vision: Machine perception based on vision or to use computers to emulate human vision. Image recognition is a little like this. 2019/5/22 Digital Image Processing

1.5 What can digital image processing do? . Digitizing an image ( convert an continuous image to a digital one) . Enhancing an image ( Let an image better suit for a specific application) . Restoring an image ( Recover a damaged image) . Compressing an image ( Store it with less bytes ) . Segmenting an image ( Partition objects in an image from background ) . Recognizing an image ( Tell what the objects are in an image ) 2019/5/22 Digital Image Processing

1.5.1 Digitizing an image It is the first step of digital image processing Y . Sample ( like these grids) . quantization F(x,y) X x 2019/5/22 Digital Image Processing

1.5.2 Enhancing an image . Original Image Enhanced Image 2019/5/22 Digital Image Processing

1.5.3 Restoring an image When an image damaged, we can recover it torn Cracked parts 2019/5/22 Digital Image Processing

Restoring an image Restored image Original image Wrinkle 2019/5/22 Digital Image Processing

Restoring an image Restored image Original image Torn 2019/5/22 Digital Image Processing

1.5.4 Compressing an image Original image 257kb Compressed image 147kb Redundant Info. 2019/5/22 Digital Image Processing

1.5.5 Segmenting an image Original image Segmented image 2019/5/22 Digital Image Processing

Segmenting an image Original image Segmented image 2019/5/22 Digital Image Processing

Segmenting an image ( Coffee beans separation ) 2019/5/22 Digital Image Processing

1.5.6 Recognizing an image Take car license plate recognition as an example. 2019/5/22 Digital Image Processing

1.6 Digital image processing and computer graphics. . The differences between them can be shown as follows. Image1 Image2 image processing Data Image3 Computer Graphics Image1 and Image2 are different: Image2 is gotten by processing image1; Image3 is produced or generated by converting data, which maybe a virtual image; Some examples are as follows. 2019/5/22 Digital Image Processing

Some examples about their differences. A simple example for computer graphics is that when we input the center coordinates (x,y) and a radius R, a circle ( image) can be produced by computer graphics system. R (x,y) 2019/5/22 Digital Image Processing

Combination of computer graphics and image processing Now computer graphics and image processing often mixes in some applications. ---- 3D Geometric Modeling Based on Image Sometimes it is easier to pick up some geometric information from an image when modeling ---- Rendering Based on Image Sometimes it is easier to pick up some surface information such as colors, textures and so on from an image directly. An example is D human face modeling and expressional animation 2019/5/22 Digital Image Processing

An example . From a general 3D human face model to specific human face model Input two photos From someone Define some feature points The second transformation Apply first transformation by interactive operations 2019/5/22 Digital Image Processing

From a general 3D model to specific human face model . Rendering Subtle transformation A true 3D model We take the human face as an elastomer and set up an elastomeric equation for computing all other point shifts according to above feature points. 2019/5/22 Digital Image Processing

Another example . Human Face expressional animation As the same as constructing face model, we established human face expressional animation model based on an elastomer motion. We have implemented two kinds of animations, one is eyes blinking, another is mouth opening and closing. Here are some equations from our method for the eyes blinking animation. 2019/5/22 Digital Image Processing

Here shows a result of eyes blinking animation 2019/5/22 Digital Image Processing

Here shows a result of mouth opening and closing 2019/5/22 Digital Image Processing

1.7 The flow of a typical digital image processing system Processed image Original image Camera or Scanner Pre- processing Enhancement Processing Restoration Compression Recognition Analysis An interpretation Control Signals Digitization Controlled Devices 2019/5/22 Digital Image Processing

1.8 The elements of a digital image processing system Image acquisition: Digital camera or scanner or video camera; Image storage: all kinds of digital memory, such as hard disk, tape, optical disk and so on; Image processing: Computers with software; Image display: Displayer or all kinds of hardcopy devices. 2019/5/22 Digital Image Processing

1.9 Some Applications of digital image processing It is widely used in industry,medical image, commerce, entertainment and so on. (1) Industry monitoring system e.g. Temperature control , automatically adjust temperature based on the color in the flame image. 2019/5/22 Digital Image Processing

(2) Fingerprint recognition 2019/5/22 Digital Image Processing

Fingerprint analysis 2019/5/22 Digital Image Processing

. Fingerprint analysis 2019/5/22 Digital Image Processing

Application of Fingerprint System . Cracking a criminal case with the help of fingerprint recognition, . Personal Identity Card, Store the fingerprint image in the ID card. . Entry management --- The conference permission entrance --- Large park with multi-entrances 2019/5/22 Digital Image Processing

(3) Traffic Management The key is car license plate recognition based on image --- Acquiring the image of a car license plate Using camera or video camera --- Enhancement processing Adjusting the distribution of the gray level in an image --- Segmentation Segmenting letters or digitals in the plate --- Recognition Telling what the letters or digitals are 2019/5/22 Digital Image Processing

(4) Traffic Control . It can be widely used to the following aspects .. Charge automatically on freeway --- Auto-record the car license plate --- Distinguish the type of car --- Recognize the plate --- Connecting the credit card system automatically 2019/5/22 Digital Image Processing

(5) Traffic Control .. Park management Automatically record the car license plate and recognize it and control passing-bar to switch on or off. .. Monitor the driver with over-speed on freeway automatically record the car license plate with over-speed and recognize it. 2019/5/22 Digital Image Processing

(6) Entertainment An example --- Human face beautifying 2019/5/22 Digital Image Processing

2019/5/22 Digital Image Processing

1.10 Some examples of Using DIP Based on EM spectrum The electromagnetic spectrum arranged according to energy per photon. (2) X-ray and Visual bands of spectrum are the most familiar images in actual application, such as X-ray in medical inspection and so on. 2019/5/22 Digital Image Processing

(3) Gamma-Ray Imaging Nuclear medicine: Inject a patient with a radioactive isotope that can emit gamma-ray. It is used in locating sites of bone pathology,such as infection or tumors. PET --- Positron Emission Tomograph 2019/5/22 Digital Image Processing

(4) X-ray Imaging Be widely used in Medical diagnostics, Industry, Astronomy and so on. When X-rays penetrate an objects, there is a different amount of absorption for different parts in the object , so an image is generated in the film to be sensitive to X-ray energy. 2019/5/22 Digital Image Processing

(5) Imaging in the Ultraviolet Band Applications of ultraviolet “light” include lithography,industrial inspection, microscopy,lasers,biological imaging,and astronomical observations. i) Ultraviolet light is used in fluorescence microscopy. ii) Fluorescence microscopy is an excellent method for studying material that can be made to fluorescene. 2019/5/22 Digital Image Processing

(6) Imaging in the Visible and Infrared Bands The visual band of the electromagnetic spectrum is the most familiar in our activities. So their applications are also the widest compared with other bands. And infrared band is often viewed visual light. Here we show some applications of the visual light in light Microscopy,astronomy,remote sensing,industry,and law enforcement. i) Some examples of images obtained with a light microscope. 2019/5/22 Digital Image Processing

These examples range from pharmaceuticals and micro- inspection to materials characterization. 2019/5/22 Digital Image Processing

ii) Some applications are from remote sensing. Here shows the so-called thematic bands in NASA’s LANDSAT satellite. 2019/5/22 Digital Image Processing

We obtained some images including features such as building, roads,vegetation,and a major river (the Potomac) going through the city in Washington D.C according to the Table 1.1. 2019/5/22 Digital Image Processing

iii) Weather observation and prediction also are major
Digital Image Processing iii) Weather observation and prediction also are major applications of multi-spectral imaging from satellites. 2019/5/22 Digital Image Processing

iv) An application of infrared imaging from the Nighttime Lights of the World data set, which provides a global inventory of human settlements. 2019/5/22 Digital Image Processing

v) The applications in automated visual inspection of manufactured goods. (a) A circuit board. (b) Packaged pills. (c) Bottles. (d) Bubbles in clear-plastic product. (e) Cereal. (f) Image of intraocular implant. 2019/5/22 Digital Image Processing

vi) Some other applications of the visual spectrum. 2019/5/22 Digital Image Processing

(7) Imaging in the Microwave Band A typical application in the microwave band is radar. 2019/5/22 Digital Image Processing

(8) Imaging in the Radio Band The major applications in the radio band are in medicine and astronomy. In medicine radio waves are used in magnetic resonance imaging (MRI). 2019/5/22 Digital Image Processing

Comparison with other bands 2019/5/22 Digital Image Processing

(9) Examples in which Other Imaging Modalities Are Used
Digital Image Processing (9) Examples in which Other Imaging Modalities Are Used Acoustic imaging, electron microscopy and synthetic imaging are also important besides imaging in the electromagnetic spectrum. Imaging using “sound” finds application in geological exploration, industry, and medicine. 2019/5/22 Digital Image Processing

The best known applications of the ultrasound imaging are in medicine, especially in obstetrics. 2019/5/22 Digital Image Processing

A transmission electron microscope (TEM) works much like a slide projector. A scanning electron microscope (SEM) scans the electron beam and records the interaction of beam and the sample at each location. Electron microscopes are capable of very high magnification. 2019/5/22 Digital Image Processing

Lastly, images generated by computers. 2019/5/22 Digital Image Processing

1.11 How to digitize an image For an image we must digitize it so that it can be processed by computers. For an image, we usually use the intensity function f(x,y) to represent it. (x,y) --- the location of a point in the image; f (x,y) --- the intensity of the point (x,y); It is obvious that 0< f(x,y) < 2019/5/22 Digital Image Processing

A simple model is f(x,y)= i(x,y)r(x,y) i(x,y) --- intensity of the incident light 0 < i (x,y) < r(x,y) --- the coefficient of the reflection, depend on the object light casts 0 < r(x,y) < 1 2019/5/22 Digital Image Processing

Take a picture as an example. Y f (x,y) X 2019/5/22 Digital Image Processing

Sampling --- Digitize the spatial coordinates ( pixel ) Quantizing --- Digitize the intensity function f (x,y) An image processed by sampling and quantizing is called the digital image. It is also the procedure from a continuous image to a discrete one. Uniform sampling --- If all sampled points are equal spaces Uniform quantizing --- If all grey-level intervals are the same ( From the darkest to the brightest ) 2019/5/22 Digital Image Processing

Suppose there are N pixels along horizontal direction X and M pixels along vertical direction Y. and there are L gray levels, a digital image cab be represented by the following matrix. 2019/5/22 Digital Image Processing

For any point (x,y) in the digital image Usually, and So the number, b, of bits required to store a digital image: 2019/5/22 Digital Image Processing

As for the quality of a digital image, the larger are M, N and L, the better is the image. For a square image, we have M=N, so Usually 2019/5/22 Digital Image Processing

Question: What will happen to the image when we change the value of M or N? What will happen to the image when we change the value of L or k? We modify M and N, let them decrease gradually, but k is not be changed, let M=N=1024, M=N=512, M=N=256, M=N=128, M=N=64 and M=N=32, the results are shown as follows respectively. 2019/5/22 Digital Image Processing

When M and N are not changed, we let k=8,7 6,5,4,3,2,1 respectively, that is L=256, 128, 64, 32, 16, 8, 4 and 2 respectively, we get all images as shown on the right. 2019/5/22 Digital Image Processing

If we change M, N and k simultaneously, what will happen? Take the following three pictures for an example. 2019/5/22 Digital Image Processing

The result can be described as the following graph. 2019/5/22 Digital Image Processing

Questions & Problems 1. What is DIP? 2. What are differences between DIP and Computer graphics? 2019/5/22 Digital Image Processing

Digital Image Processing

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