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Multi-Histogram Equalization Methodsfor Contrast Enhancement and Brightness Preserving
David Menotti, Laurent Najman, Jacques Facon, and Arnaldo de A. ArajoIEEE Transactions on Consumer Electronics, Vol. 53, No. 3, AUGUST 2007
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Histogram equalization()
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Histogram equalization(2)
Change the mean brightness of the image to the middle level of the gray_level range
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Multi-Histogram equalizationConsists of decomposing the input image into several sub-images,and then applying the Histogram equalization to each one
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natural numbers integer numbers is a sub set of0 x < m , 0 y < n ,
Image I: to L={0,..., L1} L is typically 256 ,a point(x,y) , l=I(x,y) is called the level of the point (x, y) in I .0 ls lf
- 0 lsllf
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Shannon's Entropy ( )
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Minimum Within-Class Variance MHE (MWCVMHE)
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Minimum Middle Level Squared Error MHE (MMLSEMHE).(ls+lf)/2, O[ls,lf ]
middle value of the image
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Classical HE method : uniform histogram of the output image
,ls l lf
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Other MethodBrightness Bi-HE Method (BBHE) Dualistic Sub-Image HE Method (DSIHE)Minimum Mean Brightness Error Bi-HE Method(MMBEBHE)Recursive Mean-Separate HE Method (RMSHE)
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TEST RESULTS
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TEST RESULTS