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.