Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images.
When the probability of measuring a particular value of some quantity varies inversely as a power of that value, the quantity is said to follow a power law, also known variously as Zipf's law or the Pareto distribution. (How could this phrase applied in image enhancement techniques? )
Image Enhancement stretches the contrast of the image (from limited value of intensities to full scale).
The power law transformations is defined as :
S(x,y)=c. f(x,y)^γ
where symbol γ is called gamma, due to which this transformation is also known as gamma transformation. Variation in the value of γ, varies the enhancement of the images.
Note: 1). Different display devices / monitors have their own gamma correction, they display their image at different intensity, that’s why, we need to change the intensities as per requirement of the display.
2). Depending on the requirement of the display, some times enhancer requires to use different scaling factor for a particular range of intensities. (e.g. piece wise linear transformation)
The Gamma transformation of a given image is among the so-called power-law transformation family. Since image gray level values are positive, the transformation output does not vary inversely with the original value. It performs gray level stretching.
Perhaps our recent published open access paper would be of some help:
Article On Box-Cox Transformation for Image Normality and Pattern Cl...
- Badges
- Science topic
- Similar topics
- Computer Science
- Images