1. Chapter 1: Introduction

2. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda2 Text book & Reference book Textbook: Rafael C. Gonzalez and Richard E. Woods, "Digital Image Processing, 2nd edition", Prentice Hall, 2001. Reference book: Rafael C. Gonzalez and Richard E. Woods, "Digital Image Processing", Addison Wesley 1993. Milan Sonka, Vaclav Hlavac and Roger Boyle, "Image Processing Analysis, and Machine Vision 2nd edition", PWS Publishing, 1998.

3. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda3 Overview Early days of computing, data was numerical. Later, textual data became more common. Today, many other forms of data: voice, music, speech, images, computer graphics, etc. Each of these types of data are signals. Loosely defined, a signal is a function that conveys information.

4. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda4 As long as people have tried to send or receive through electronic media : telegraphs, telephones, television, radar, etc. there has been the realization that these signals may be affected by the system used to acquire, transmit, or process them. Sometimes, these systems are imperfect and introduce noise, distortion, or other artifacts. Relationship of Signal Processing to other fields

5. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda5 Understanding the effects these systems have and finding ways to correct them is the fundamental of signal processing. Sometimes, these signals are specific messages that we create and send to someone else (e.g., telegraph, telephone, television, digital networking, etc.). That is, we specifically introduce the information content into the signal and hope to extract it out later.

6. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda6 Sometimes, these man-made signals are encoding of natural phenomena (audio signal, acquired image, etc.) But sometimes we can create them from scratch (speech generation, computer generated music, computer graphics). Finally, we can sometimes merge these technologies together by acquiring a natural signal, processing it, and then transmitting it in some fashion.

7. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda7 Acquire natural Image Enhance The Picture Compress For Transmission Encode and Transmit Over Digital N/W Sender: Recipient: Transmitted code for image DecodedDecompressed Interpreted in some fashion by our brain Received by eyes Displayed to create another Signal (visible light of the display) From acquisition to interpretation, the initial signal may be transformed, modified, and retransmitted numerous times.

8. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda8 Concerned fields: Digital Communication Compression Speech Synthesis and Recognition Computer Graphics Image Processing Computer Vision

9. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda9 What is Image Processing? Image processing is a subclass of signal processing concerned specifically with pictures. Improve image quality for human perception and/or computer interpretation. ImageImage ProcessingBetter Image

10. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda10 Several fields deal with images Computer Graphics : the creation of images. Image Processing : the enhancement or other manipulation of the image – the result of which is usually another images. Computer Vision: the analysis of image content.

11. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda11 Several fields deal with images Computer Vision, Image Processing and Computer Graphics often work together to get amazing result.

12. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda12 2 Principal application areas Improvement of pictorial information for human interpretation Processing of image data for storage, transmission, and representation for autonomous machine perception

13. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda13 Ex. of fields that use DIP Categorize by image sources: Radiation from the Electromagnetic spectrum Acoustic Ultrasonic Electronic (in the form of electron beams used in electron microscopy) Computer (synthetic images used for modeling and visualization)

14. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda14 Radiation from EM spectrum EM waves = a stream of mass-less (proton) particles, each traveling in a wavelike pattern and moving at the speed of light. Spectral bands are grouped by energy per photon Gamma rays, X-rays, Ultraviolet, Visible, Infrared, Microwaves, Radio waves

15. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda15 Gamma-Ray Imaging Nuclear Image (a) Bone scan (b) PET (Positron emission tomography) image Astronomical Observations. (c) Cygnus Loop Nuclear Reaction (d) Gamma radiation from a reactor valve

16. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda16 X-ray Imaging Medical diagnostics (a) chest X-ray (familiar) (b) aortic angiogram (c) head CT Industrial imaging (d) Circuit board Astronomy (e) Cygnus Loop

17. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda17 Imaging in Ultraviolet Band Lithography Industrial inspection Microscopy (fluorescence) (a) Normal corn (b) Smut corn Lasers Biological imaging Astronomical observations (c) Cygnus Loop

18. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda18 Imaging in Visible and Infrared Bands Astronomy Light microscopy pharmaceuticals (a). taxol (anticancer agent) (b). Cholesterol Micro-inspection to materials characterization (c). Microprocessor (d). Nickel oxide thin film (e). Surface of audio CD (f). Organic superconductor

19. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda19 Remote sensing : To monitoring environmental conditions on the planet

20. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda20 Remote sensing : Weather observation and prediction Multispectral image of Hurricane Andrew from satellites using sensors in the visible and infrared bands

21. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda21 Remote sensing : Nighttime Lights of the World (provides a global inventory of human settlements)

22. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda22

23. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda23

24. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda24 Imaging in Microwave Band Imaging radar : the only way to explore inaccessible regions of the Earth’s surface Radar image of mountains in southeast Tibet Note the clarity and detail of the image, unencumbered by clouds or other atmospheric conditions that normally interfere with images in the visual band.

25. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda25 Imaging in Radio Band Medicine Magnetic resonance image (MRI) : 2D picture of a section of the patient (any plane) (a) knee (b) spine Astronomy a b

26. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda26 Acoustic Imaging Geological applications : use sound in the low end of the sound spectrum (hundred of Hz) Mineral and oil exploration Cross-sectional image of a seismic model. The arrow points to a hydrocarbon (oil and/or gas) trap (bright spots)

27. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda27 Ultrasound Imaging Manufacturing Medicine (a) Baby (b) Another view of baby (c) Thyroids (d) Muscle layers showing lesion

28. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda28 Generated images by computer Fractals : an iterative reproduction of a basic pattern according to some mathematical rules (a) and (b) 3-D compute modeling (c) and (d)

29. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda29 3 types of computerized process Low-level : input, output are images Primitive operations such as image preprocessing to reduce noise, contrast enhancement, and image sharpening Mid-level : inputs may be images, outputs are attributes extracted from those images - Segmentation - Description of objects - Classification of individual objects High-level : Image analysis

30. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda30 Fundamental steps

31. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda31 Image Acquisition: An image is captured by a sensor (such as a monochrome or color TV camera) and digitized. If the output of the camera or sensor is not already in digital form, an analog-to digital converter digitizes it.

32. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda32 Camera Camera consists of 2 parts A lens that collects the appropriate type of radiation emitted from the object of interest and that forms an image of the real object A semiconductor device – so called charged coupled device or CCD which converts the irradiance at the image plan into an electrical signal.

33. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda33 Frame Grabber Frame grabber only needs circuits to digitize the electrical signal from the Imaging sensor to store the image in the memory (RAM) of the computer.

34. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda34 Image Enhancement To bring out detail is obscured, or simply to highlight certain features of interest in an image.

35. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda35 Image Restoration Improving the appearance of an image Tend to be based on mathematical or probabilistic models of image degradation

36. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda36 Color Image Processing Gaining in importance because of the significant increase in the use of digital images over the Internet However, our lecture is limited to gray level image processing

37. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda37 Wavelets Foundation for representing images in various degrees of resolution. Used in image data compression and pyramidal representation (images are subdivided successively into smaller regions)

38. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda38 Compression Reducing the storage required to save an image or the bandwidth required to transmit it. Example : JPEG (Joint Photographic Experts Group) image compression standard.

39. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda39 Morphological processing Tools for extracting image components that are useful in the representation and description of shape.

40. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda40 Image Segmentation C omputer tries to separate objects from the image background. It is one of the most difficult tasks in DIP. A rugged segmentation procedure brings the process a long way toward successful solution of an image problem. Output of the segmentation stage is raw pixel data, constituting either the boundary of a region or all the points in the region itself.

41. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda41 Representation & Description Representation : make a decision whether the data should be represented as a boundary or as a complete region. - Boundary representation : focus on external shape characteristics, such as corners and inflections. - Region representation : focus on internal properties, such as texture or skeleton shape.

42. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda42 Representation & Description

43. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda43 Recognition & Interpretation Recognition : the process that assigns a label to an object based on the information provided by its descriptors. Interpretation : assigning meaning to an ensemble of recognized objects.

44. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda44 Knowledge base A problem domain detailing regions of an image where the information of interest is known to be located. Help to limit the search

45. October 11, 2015Prof S. D. Joshi, EC Dept., VGEC,Chandkheda45 Not all the processes are needed. Ex. Postal Code Problem