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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 - PowerPoint PPT Presentation
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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- Power law transformation- Dynamic range compression- Bit plane Slicing.- Gray level Slicing.
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.
Approaches
Image Enhancement
Spatial Domain Frequency Domain
Point Processing
Filtering OR Masking
Approaches
• Spatial domain – direct manipulation of pixel.
• Frequency domain – Manipulation in frequency plane
Spatial domain 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).
f(x, y).x
y
Spatial domain(cont.)
• Point processing : -- Independent of neighbors
• Masking : -- based on small sub image.
Image negative
N = Gmax - O
Contrast Stretching
Contrast Stretching
• Factor that causes low contrast images Lack of dynamic range. Poor illumination
• Algorithm• Implementation
Power law Transformations
Power law Transformations
Compression of dynamic range
Compression of dynamic Range
• s = c . log(1+|r|)• Log function scales [0,10^6] to [0,6].• c=255/6.
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.
Gray level Slicing
• Separating gray level range of interest to different level so that the region is highlighted.
Histogram• The histogram of a digital image with intensity
levels in the range [0,L-1] is a discrete function h(rk)=nk where,- 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.
Histogram
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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