slide1 n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Digital Image Processing PowerPoint Presentation
Download Presentation
Digital Image Processing

Loading in 2 Seconds...

play fullscreen
1 / 42

Digital Image Processing - PowerPoint PPT Presentation


  • 202 Views
  • Uploaded on

Introduction and Digital Image Fundamentals. Digital Image Processing. Bundit Thipakorn, Ph.D. Computer Engineering Department. Fields of Computer Image. Computer Graphics ( Image Synthesis) Image Processing and Image Analysis Computer Vision. Computer Graphics.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Digital Image Processing


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. Introduction and Digital Image Fundamentals Digital Image Processing Bundit Thipakorn, Ph.D. Computer Engineering Department

    2. Fields of Computer Image • Computer Graphics ( Image Synthesis) • Image Processing and Image Analysis • Computer Vision

    3. Computer Graphics A methodology of the creation of images using a computer. = Input Output Computer Graphics 3-D Model 2-D Image

    4. Image Processing A process of manipulating an image to produce another image. = Input Output Image Processing 2-D Image 2-D Image

    5. ImageProcessing (cont’d.) Output of image processing is to be used by human being . Output Image Input Image • Correcting • Improving • Analyzing • etc.

    6. Image Analysis A process of manipulating an image to some measurements. = Input Output Image Analysis 2-D Image Measurements Out

    7. Computer Vision Object

    8. What is Signal? Typically, a signal carries information about the behavior or nature of the phenomenon. Definition 1: Signalis a pattern of variations of a measurable quantity that is a function of one or more independent variables such as time (t) and space (x and y).

    9. Signal? (cont’d.) S(t) = at S(t) = at2 + bt + c S(t) = Asin(wt+f) S(x,y) = ax + by + cxy Signal can be represented mathematically as: Where a, b, c, A, w, and f are constant values. The function which is used to describe a signal is called the representation of the signal.

    10. A Speech Signal 4 x 10 1.5 1 A speech signal is a mechanical signal representing the air pressure and carries voice information. 0.5 0 -0.5 -1 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Amplitude Time

    11. Digital Images (2-D Signals) A digital image is a light signal representing the light intensity and carries visual information .

    12. What Is a Digital Signal? Digital Signal: a signal having a set of discrete values at certain specific values of time. i.e. • Discrete Time • Discrete Amplitude

    13. Digital Signal? (Cont’d.) The digital signal is generated from the analog signal using the following steps: 1. Sampling: Discrete Time 2. Quantizing: Discrete Amplitude

    14. Digital Signal? (Cont’d.) A sampling process is the process to sample an analog signal at a certain period of time called the sampling interval. A quantization process is the process to round up the values of the discrete-time signal to a finite set of possible values. Thus, the quantization process will convert a d-t continuous-valued signal into a d-t discrete-valued (digital) signal.

    15. 10 0 -10 -0.01 -0.008 -0.006 -0.004 -0.002 0 0.002 0.004 0.006 0.008 0.01 10 0 -10 -20 -15 -10 -5 0 5 10 15 20 2 0 -2 -20 -15 -10 -5 0 5 10 15 20 Analog-to-Digital (A/D) Analog Signal Sampling Discrete-Time Signal Quantizing Digital Signal

    16. Digitization = A process to convert the analog signal to encoded digital signal. Encoding Discrete-Time Signal Analog Signal Digital Signal Sampling Quantizing Encoded Digital Signal

    17. Digital Sound Recording Sampling Quantizing Encoding

    18. Digital Image Sampling Grid Continuous Image

    19. Digital Image (cont’d.) Digital Image

    20. Digital Image Formation Light source Digital Signal Object Electrical Signal Digitizer Video Camera Digital Image Form, f(x,y) Analog Image Form Optical Image Form

    21. Digital Image Formation (cont’d.) f(x,y) = i(x,y)r(x,y) Where i(x,y) = illumination component 0 < I(x,y) < ∞ r(x,y) = reflectance component 0 < r(x,y) < 1 r(x,y) = 0 Total absorption Total reflectance r(x,y) = 1

    22. Representing Digital Images A 2-D data space, f(x,y).

    23. Representing Digital Images (cont’d.) Gray Scale 0 Y 1 2 3 4 5 6 7 8 9 10 X 11

    24. Representing Digital Images (cont’d.) Gray Scale Pixel 0 Y 1 1 1 1 1 10 11 2 1 1 1 1 3 1 1 1 1 4 1 5 1 6 1 7 1 0 0 0 8 0 2 2 2 10 11 2 3 9 X 10 Pixel (x, y, Gray Scale) 11

    25. Quality of Digital Image Effect of Resolution on Image Quality As resolution increases, image quality will level off.

    26. Resolution 1. The number of pixels (sampling points) used to represent the digital image. 2. Dots per Inch ( DPI )

    27. Resolution 80 x 60 40 x 30

    28. Resolution 320 x 240 160 x 120

    29. Quality of Digital Image(cont’d.) 24-bit JPEG 8-bit GIF Effect of Bit Depth on Image Quality

    30. Bit Depth The number of bits used to define the value of each pixel. Let n = the number of bits used The number of gray scale = 2n

    31. Bit Depth 1 Bit of Gray (2) 2 Bits of Gray (4)

    32. Bit Depth 4 Bit of Gray (16) 8 Bits of Gray (256)

    33. Quality of Digital Image(cont’d.) Image Enhancement

    34. Quality of Digital Image(cont’d.) GIF JPEG Effects of Lossy Compression on Text

    35. The Hierarchical Image Pyramid Operations Image Representation Feature Extraction Features/ Object High Level Transform Segmentation Edge Detection Spectrum Segments Edge/Lines Preprocessing Neighborhood/ Subimage Raw Image Data Pixel Low Level

    36. Elements of Image Analysis Low-Level Processing • Non intelligence process; • Image formation: create a digital image; • Image Enhancement: improve the quality of the image or enhance particular aspects within the image; • Image Restoration: recover the original image from the degraded image.

    37. Image Analysis (cont’d.) Intermediate-Level Processing • Segmentation: partition an image into meaningful regions corresponding to part of, or the whole of objects within the image; • Representation: identify inherent features or characteristics of objects found within an image;

    38. Image Analysis (cont’d.) Intermediate-Level Processing (cont’d.) • Description: describe the features representing an objects. High-Level Processing • Recognition and Interpretation; • Intelligent cognition.

    39. Elements of Image Analysis Low-Level Processing Intermediate-Level Processing Problem Domain Image Acquisition Preprocessing Segmentation Representation and Description Result Recognition and Interpretation High-Level Processing Knowledge Base

    40. Brightness Perception of Human being • The brightness perception of human being is not a simple function of intensity. • Subjective brightness is a logarithmic function of the light intensity incident on the eye.

    41. Brightness Perception of Human being Mach Band Effect

    42. Brightness Perception of Human being Simultaneous Contrast