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Image Enhancement in Spatial Domain

Image Enhancement in Spatial Domain. Presented by : - Mr. Trushar Shah. ME/MC Department, U.V.Patel College of Engineering, Kherva. Today’s topics. What is image enhancement? Approaches. Image processing in spatial domain. Implementation - Image negative - Contrast Stretching

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Image Enhancement in Spatial Domain

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  1. Image Enhancement in Spatial Domain Presented by : - Mr. Trushar Shah. ME/MC Department, U.V.Patel College of Engineering, Kherva

  2. Today’s topics • What is image enhancement? • Approaches. • Image processing in spatial domain. • Implementation - Image negative - Contrast Stretching - Power law transformation - Dynamic range compression - Bit plane Slicing. - Gray level Slicing.

  3. What is Image Enhancement? • To process an image so that the result is more suitable than the original image for a specific application. • Enhancement is the subjective process.

  4. Approaches Image Enhancement Frequency Domain Spatial Domain Point Processing Filtering OR Masking

  5. Approaches • Spatial domain – direct manipulation of pixel. • Frequency domain – Manipulation in frequency plane

  6. Spatial domain f(x, y). x • Image can be modeled by a continuous function of two variables : (x, y) co-ordinates of point/pixel. • The image function values correspond to the brightness/intensity at image point and generally denoted by f(x, y). y

  7. Spatial domain(cont.) • Point processing : - - Independent of neighbors • Masking : - - based on small sub image.

  8. Image negative

  9. N = Gmax - O

  10. Contrast Stretching

  11. Contrast Stretching • Factor that causes low contrast images • Lack of dynamic range. • Poor illumination • Algorithm • Implementation

  12. Power law Transformations(g>1)

  13. Power law Transformations(g<1)

  14. Compression of dynamic range

  15. Compression of dynamic Range • s = c . log(1+|r|) • Log function scales [0,10^6] to [0,6]. • c=255/6.

  16. Bit plane slicing • Separating each bit from pixel gray level, and gathering same for all pixel will generate bit plane. • Monochrome images are made of the 8-bit planes.

  17. Gray level Slicing • Separating gray level range of interest to different level so that the region is highlighted.

  18. Histogram • The histogram of a digital image with intensity levels in the range [0,L-1] is a discrete function h(rk)=nkwhere, - rk is the kth intensity value. - nk is the number of pixel with intensity rk. • Normalized Histogram:- - A normalized histogram is given by p(rk) = nk/MN. - The sum of all components of normalized histogram is 1.

  19. Histogram

  20. Conclusion for Histogram Processing • The whole span of gray levels should be used. • Number of pixels for all the gray levels, should be equal. OR • The probability of occurrence of all gray level should be uniform.

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