Image enhancement based-on local statistics using colfilt
Ideas from Gonzalez's dip book.test image is downloaded from its webpage!I provide two functions with the same function. The first invoked by NLFILTER and second invoked by COLFILT.
In this case, file named demo_locstat2.m using mylocstat2 is much fast than demo_locstat.m using mylocstat. Please pay more attention on the different codeing styles between mylocstat.m and mylocstat2.m.
MYLOCSTAT - perform single-back gray value imadjustation based on local statistics for sliding block operation.
Motivation: try local statistics enhancement operation.
Parameters:
Iloc - the local neighbourhood of image to be processed.
M - the global mean of image's gray values.
D - the global variance of image's gray values.
E - the ehancement constant
k - the 1x3 sized threshold vector:
- k(1) is mean threshold
- k(2) and k(3) are variance threshold
MYLOCSTAT2 - perform single-back gray value imadjustation based on local statistics for sliding block operation.
Motivation: try local statistics enhancement operation.
Parameters:
Icol - the matrix includes the columns of all local neighbourhoods.
M - the global mean of image's gray values.
D - the global variance of image's gray values.
E - the ehancement constant
k - the 1x3 sized threshold vector:
- k(1) is mean threshold
- k(2) and k(3) are variance threshold
Citar como
Xi-Nian Zuo (2025). Image enhancement based-on local statistics using colfilt (https://la.mathworks.com/matlabcentral/fileexchange/9129-image-enhancement-based-on-local-statistics-using-colfilt), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxCategorías
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement >
- Image Processing and Computer Vision > Image Processing Toolbox > Get Started with Image Processing Toolbox >
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| Versión | Publicado | Notas de la versión | |
|---|---|---|---|
| 1.0.0.0 | Add screenshots! |
