transformed
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input
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Image Processing: Transformations, Filters, and Derivatives, Summaries of System Analysis and Design
Image processing techniques, including intensity transformations, linear and nonlinear spatial filters, and the definition of derivatives in digital functions. It covers topics such as leibniz’s rule, normalization of filters, and the use of box filters. Examples of transformations and their effects are provided.
Typology: Summaries
2019/2020
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transformed
output
input
The smallest possible neighborhood is of size 1 × 1. In this case, g depends only on the
value of f at a single point (x, y) and T in Eq. (3-1) becomes an intensity (also called a
gray-level, or mapping) transformation function of the form
Example
We use a transformation of this type to expand the values of dark pixels in an image, while compressing the higher-level values. The opposite is true of the inverse log (exponential) transformation
The main disadvantage of these functions is that their specification requires considerable user input