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• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• Digital Image Processing
• ### Dip

1. 1. DIGITAL IMAGE PROCESSING ANKU SAINI 1090516308/10/12 Digital Image Processing 1
2. 2. Why do we need to study DIP? Interest in digital image processing methods stems from two aspects: 1) Improve images for human interpretation; 2) Process images, include storage, transmission.08/10/12 Digital Image Processing 2
3. 3. 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.08/10/12 Digital Image Processing 3
4. 4. 1.2 The Origins of Digital image Processing. The first application was in newspaper industry in 1920s08/10/12 Digital Image Processing 4
5. 5. Digital Image Processing, 2nd ed. Digital Processing, 2nd ed. www.imageprocessingbook.com Chapter 1: IntroductionThey were not real image processing, only image encoding and printingand some improvements. © 2002 R. C. Gonzalez & R. E. WoodsIn 1960s, computer and its programming were brought into, the trueimage processing began.Two important events push forward digital image processing.1) Space Program --- First Moon Probe ( America, in 1964);2) In medicine --- CAT or CT (Computer Axial Tomography early 1970s) Using X-rays generates image. 08/10/12 Digital Image Processing 5
6. 6. 1.3 Objectives of digital image processing1.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. 08/10/12 Digital Image Processing 6
7. 7. 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 processingand computer vision. Computer vision: Machine perception based on vision or to usecomputers to emulate human vision. Image recognition is a little likethis. 08/10/12 Digital Image Processing 7
8. 8. 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 )08/10/12 Digital Image Processing 8
9. 9. 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 08/10/12 Digital Image Processing 9
10. 10. 1.5.2 Enhancing an image.Original Image Enhanced Image 08/10/12 Digital Image Processing 10
11. 11. 1.5.3 Restoring an imageWhen an image damaged, we can recover it torn Cracked parts08/10/12 Digital Image Processing 11
12. 12. 1.5.4 Compressing an image Original image 257kb Compressed image 147kbRedundant Info. 08/10/12 Digital Image Processing 12
13. 13. Segmenting an image Original image Segmented image08/10/12 Digital Image Processing 13
14. 14. 1.5.6 Recognizing an imageTake car license plate recognition as an example. 08/10/12 Digital Image Processing 14
15. 15. 1.6 Digital image processing and computer graphics.. The differences between them can be shown as follows. Image1 Image2 image processing Data Image3 Computer GraphicsImage1 and Image2 are different: Image2 is gotten by processing image1;Image3 is produced or generated by converting data, which maybe avirtual image; Some examples are as follows. 08/10/12 Digital Image Processing 15
16. 16. Some examples about their differences.A simple example for computer graphics is that when we input thecenter coordinates (x,y) and a radius R, a circle ( image) can beproduced by computer graphics system. R (x,y) 08/10/12 Digital Image Processing 16
17. 17. 1.7 The flow of a typical digital image processing systemOriginal Processed imageimage Camera or Pre- An interpretation Processing Scanner processing Control Signals Digitization Enhancement Restoration Controlled Devices Compression Recognition Analysis 08/10/12 Digital Image Processing 17
18. 18. 1.8 The elements of a digital image processing systemImage 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.08/10/12 Digital Image Processing 18
19. 19. 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.08/10/12 Digital Image Processing 19
20. 20. (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 are08/10/12 Digital Image Processing 20
21. 21. (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 08/10/12 Digital Image Processing 21
22. 22. (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.08/10/12 Digital Image Processing 22
23. 23. (6) EntertainmentAn example --- Human face beautifying08/10/12 Digital Image Processing 23
24. 24. 1.10 Some examples of Using DIP Based on EM spectrum(1) 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. 08/10/12 Digital Image Processing 24
25. 25. (3) Gamma-Ray ImagingNuclear medicine: Inject a patient with a radioactive isotope that can emitgamma-ray. It is used in locating sites of bone pathology,such as infectionor tumors.PET --- Positron Emission Tomograph 08/10/12 Digital Image Processing 25
26. 26. 08/10/12 Digital Image Processing 26
27. 27. (4) X-ray ImagingBe widely used in Medical diagnostics, Industry, Astronomy and so on.When X-rays penetrate an objects, there is a different amount of absorptionfor different parts in the object , so an image is generated in the film to besensitive to X-ray energy. 08/10/12 Digital Image Processing 27
28. 28. 08/10/12 Digital Image Processing 28
29. 29. (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.08/10/12 Digital Image Processing 29
30. 30. (6) Imaging in the Visible and Infrared BandsT 08/10/12 Digital Image Processing 30
31. 31. These examples range from pharmaceuticals and micro- inspection to materials characterization.08/10/12 Digital Image Processing 31
32. 32. iii) Weather observation and prediction also are major applications of multi-spectral imaging from satellites.08/10/12 Digital Image Processing 32
33. 33. (7) Imaging in the Microwave Band A typical application in the microwave band is radar.08/10/12 Digital Image Processing 33
34. 34. (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).08/10/12 Digital Image Processing 34
35. 35. Comparison with other bands08/10/12 Digital Image Processing 35
36. 36. 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) < ∞08/10/12 Digital Image Processing 36
37. 37. 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) < 108/10/12 Digital Image Processing 37
38. 38. Take a picture as an example. Yf (x,y) X 08/10/12 Digital Image Processing 38
39. 39. Sampling --- Digitize the spatial coordinates ( pixel )Quantizing --- Digitize the intensity function f (x,y)An image processed by sampling and quantizing is calledthe digital image.It is also the procedure from a continuous image toa discrete one.Uniform sampling --- If all sampled points are equal spacesUniform quantizing --- If all gray-level intervals are the same ( From the darkest to the brightest )08/10/12 Digital Image Processing 39
40. 40. 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 can be representedby the following matrix.  f (0,0) f (0,1) .... .... f (0, M − 1)   f (1,0) f (1,1) .... .... f (1, M − 1)    f ( x, y ) ≈  .... .... .... .... ....     .... .... .... .... ....   f ( N − 1,0)  f ( N − 1,1) f ( N − 1, M − 1)  08/10/12 Digital Image Processing 40
41. 41. For any point (x,y) in the digital image x ∈ [ 0,1,......N − 1] y ∈ [ 0,1,......M − 1] f ( x, y ) ∈ [ 0,1,......L − 1] n m k Usually, N =2 and M = 2 L= 2 So the number, b, of bits required to store a digital image: b = M ×N×k08/10/12 Digital Image Processing 41
42. 42. As for the quality of a digital image, the larger are M, Nand L, the better is the image. 2 For a square image, we have M=N, so b = N ×m U s u a l l y08/10/12 Digital Image Processing 42