×
Aiming for the stars? Great, but did you have to build a rocket first.
--Your friends at LectureNotes
Close

Note for Digital Image Processing - DIP by Vj singh

  • Digital Image Processing - DIP
  • Note
  • 4 Topics
  • 1983 Views
  • 18 Offline Downloads
  • Uploaded 9 months ago
0 User(s)
Download PDFOrder Printed Copy

Share it with your friends

Leave your Comments

Text from page-1

Image Processing Lecture 1 References:1. Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", 2/E, Prentice – Hall 2001. 2. Scott E Umbaugh, “Computer Vision and Image Processing”, Prentice – Hall 1998. 3. Nick Efford, “Digital Image Processing – a practical approach using Java”, Pearson Education 2000. 4. John R Jensen, “Introductory Digital Image Processing”, 3/E. Prentice Hall, 2005. 1. Introduction An image is a picture: a way of recording and presenting information visually. Since vision is the most advanced of our senses, it is not surprising that images play the single most important role in human perception. The information that can be conveyed in images has been known throughout the centuries to be extraordinary - one picture is worth a thousand words. However, unlike human beings, imaging machines can capture and operate on images generated by sources that cannot be seen by humans. These include X-ray, ultrasound, electron microscopy, and computergenerated images. Thus, image processing has become an essential field that encompasses a wide and varied range of applications. 2. Basic definitions • Image processing is a general term for the wide range of techniques that exist for manipulating and modifying images in various ways. • A digital image may be defined as a finite, discrete representation of the original continuous image. A digital image is composed of a finite number of elements called pixels, each of which has a particular location and value. ©Asst. Lec. Wasseem Nahy Ibrahem Page 1

Text from page-2

Image Processing Lecture 1 • The term digital image processing refers to processing digital images by means of a digital computer. 3. Digital image processing and other related areas There is no general agreement regarding where image processing stops and other related areas, such as image analysis and computer vision, start. Sometimes a distinction is made by the following paradigm: • Image processing is a discipline in which both the input and output of a process are images. For example, it involves primitive operations such as image preprocessing to reduce noise and contrast enhancement. • Image analysis (also called image understanding) is in between image processing and computer vision. In this area, the process is characterized by the fact that its inputs generally are images, but its outputs are attributes extracted from those images (e.g., edges, contours, and the identity of individual objects). This area includes tasks such as image segmentation (partitioning an image into regions or objects), description of those objects to reduce them to a form suitable for computer processing, and classification (recognition) of individual objects. • Finally, computer vision is a field whose ultimate goal is to use computers to emulate human vision, including learning and being able to make inferences of recognized objects and take actions based on visual inputs. This area itself is a branch of artificial intelligence (AI) whose objective is to emulate human intelligence. ©Asst. Lec. Wasseem Nahy Ibrahem Page 2

Text from page-3

Image Processing Lecture 1 4. Types of Imaging Systems Imaging systems are varying depending on their energy source (e.g. visual, X-ray, and so on). The principal energy source for images in use today is the electromagnetic (EM) spectrum illustrated in Figure 1.1. Other important sources of energy include acoustic, ultrasonic, and electronic (in the form of electron beams used in electron microscopy). Synthetic images, used for modeling and visualization, are generated by computer. In this section we discuss briefly how images are generated in these various categories and the areas in which they are applied. Figure 1.1 the electromagnetic spectrum arranged according to energy per photon. 4.1 Gamma-ray Imaging Gamma rays are emitted as a result of collision of certain radioactive isotopes (a positron and an electron). This occurs naturally around exploding stars, and can be created easily. Images are produced from the emissions collected by gamma ray detectors. Major uses of gamma ray imaging include nuclear medicine and astronomical observations. In nuclear medicine, a patient is injected with a radioactive isotope that emits gamma rays as it decays. Figure 1.2(a) shows a major modality of nuclear imaging called positron emission tomography (PET) obtained by using gamma-ray imaging. The image in this figure shows a tumor in the brain and one in the lung, easily visible as small white masses. ©Asst. Lec. Wasseem Nahy Ibrahem Page 3

Text from page-4

Image Processing Lecture 1 (b) (a) Figure 1.2 Examples of Gamma-Ray imaging a) PET image b) Star explosion 15,000 years ago Figure 1.2(b) shows a star exploded about 15,000 years ago, imaged in the gamma-ray band. Unlike the previous example shown in Figure 1.2(a) , this image was obtained using the natural radiation of the object being imaged. 4.2 X-ray Imaging X-rays are generated using an X-ray tube (a vacuum tube with a cathode and anode). The cathode is heated, causing free electrons to be released and flowing at high speed to the positively charged anode. When the electrons strike a nucleus, a modified energy is released in the form of Xray radiation. Images are either generated by: 1) dropping the resulting energy on a film, then digitizing it or 2) dropping directly onto devices that convert X-rays to light. The light signal in turn is captured by a lightsensitive digitizing system. ©Asst. Lec. Wasseem Nahy Ibrahem Page 4

Lecture Notes