Successfully reported this slideshow.
Upcoming SlideShare
×

# Digital image fundamentals

7,125 views

Published on

This slide show gives a fundamental knowledge about dip concepts.

• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

### Digital image fundamentals

1. 1. byParesh Kamble
2. 2. Elements of Visual PerceptionDigital Image Processing is built on foundation of Mathematical and Probabilistic formulations Human Intuition & analysis plays a key role in choosing ne technique over other. Study of Human vision system is thus important.
3. 3. Structure of Human Eye
4. 4. Rod & Cone Cells
5. 5. Distribution of Rod & Cone cells
6. 6. Image sensing and AcqusitionThree principal sensor arrangement:1) Image acquisition using a single sensor
7. 7. Image sensing and AcqusitionImage Acquisition using a single sensor:
8. 8. Image sensing and Acqusition2) Image Acquisition using sensor strips:
9. 9. Image sensing and Acqusition3) Image Acquisition using sensor arrays:
10. 10. Image sensing and Acqusition
11. 11. Image sensing and Acqusition
12. 12. Image sensing and AcqusitionSimple Image formation model:o Images are denoted by 2-dimensional function of the form f( x, y).o f at spatial co-ordinates ( x, y) is positive, finite scalar quantity determinedby source of the image. 0 < f( x, y) < ∞o f( x, y) is characterized by two components: o illumination: amount of source illumination incident on scene. denoted by i( x, y) o reflectance : amount of illumination reflected by the objects in scene. denoted by r( x, y) Thus, f(x,y) = i(x,y) r(x,y) where, 0 < i(x,y) < ∞ …………….(1) & 0(total absorption)< r( x, y) < 1(total reflectance) …………….(2)
13. 13. Image sensing and AcqusitionSimple Image formation model:o Let the gray level (intensity) of a monochromatic image at any co-ordinate be denoted by: l = f(x0, y0); From equation (1) & (2) we get Lmin ≤ l ≤ Lmax where, Lmin should be positive & Lmax be finite.We have, Lmin = imin rmin & Lmax = imax rmaxThe interval [Lmin, Lmax] is called the gray (intensity) scale.We shift this interval to interval [0, L-1], where, l = 0 is black & l = L-1 is white on grey scale.
14. 14. Image Sampling & Quantization
15. 15. Image Sampling & Quantization
16. 16. Image Sampling & Quantization
17. 17. Image Sampling & QuantizationSampling: Digitizing the coordinate value.Quantization: Digitizing the amplitude value.
18. 18. Image Sampling & QuantizationSpatial & Intensity ResolutionSpacial Resolution:dpi : (dots per inch)Newspapers : 75 dpiMagazines : 133 dpiGlossy brochures : 175 dpiBooks : 2400dpi
19. 19. Image Sampling & QuantizationIntensity resolution: smallest discernible change in intensity level.Image interpolation: process of using known data to estimate the values at unknown locations. Nearest neighbor interpolation: assigns intensity of nearest neighbor in original image. Bilinear interpolation: uses 4 nearest neighbors. Bicubic interpolation: uses 16 nearest neighbors.
20. 20. High Definition (HD)Video Frame size in Pixels per Scanning Frame rate (Hz)mode pixels (W×H) image type720p 1,280x720 921,600 Progressive 23.976, 24, 25, 29.97, 30, 50, 59.94, 60, 721080i 1,920x1,080 1,036,800 Interlaced 25 (50 fields/s), 29.97 (59.94 fields/s), 30 (60 fields/s)1080p 1,920x1,080 2,073,600 Progressive 23.976, 24, 25, 29.97, 30, 50, 59.94, 60
21. 21. High Definition (HD)