The simplest thresholding methods replace each pixel in an image with a black pixel if the image intensity {\displaystyle I_{i,j}}I_{{i,j}} is less than some fixed constant T (that is, {\displaystyle I_{i,j}<T}I_{{i,j}}<T), or a white pixel if the image intensity is greater than that constant. In the example image on the right, this results in the dark tree becoming completely black, and the white snow becoming completely white
Otsu's method is used to perform automatic image thresholding.In the simplest form, the algorithm returns a single intensity threshold that separate pixels into two classes, foreground and background.
This is an implementation of a traditional Niblack local image thresholding with an integral image method, which guarantees constant computation time regardless of the neighborhood size.
The implemented Sauvola method uses integral images for fast computation of the threshold function.
Clean Image
Noise
Clean image adding Noise(image)
full Image
part(crop) image
Reconstructed image
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Gulam Kibria Chowdhury
CSE Graduate || Competitive Programmer
Sylhet, Bangladesh
Gmail: gkchowdhury101@gmail.com
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