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!"#$%&'()*%++,-$&.,/0&12%-34&&
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• Gray Levels: {0,1, … , 255}
• Number of Bins: 32
• Number of intensity levels for each bin: 256 / 32 = 8
6 12 16
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• C)("#;,D%<&0,+/)$(#"&A#;:%+&":+/&O%&(%2(%+%-/%<&OG&_)#/&)(&<):O;%P&1/0%(.,+%&/0%(%&"#G&O%&;)++&)N&,-N)("#=)-&<:%&/)&/(:-*#=)-P&
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• 3#"%(#+&#-<&,"#$%&+%-+)(+&":+/&:+:#;;G&<%#;&-)/&)-;G&.,/0&/0%&*)-/(#+/&,-&#&+*%-%&O:/&#;+)&.,/0&/0%&,"#$%&+%-+)(+`&%H2)+:(%&/)&/0%&(%+:;=-$&;,$0/&,-&/0#/&+*%-%P&&
• I^%(&/0%&2,*/:(%&0#+&O%%-&/#T%-R&/0%(% +̀&-)/0,-$&.%&*#-&<)&#O):/&.0#/&/0%&+%-+)(&(%*)(<%<a&0).%A%(R&.%&*#-&+=;;&/#T%&.0#/ +̀&/0%(%&#-<&/(G&/)&%H2#-<&/0%&<G-#",*&(#-$%&)N&/0%&,"#$%P&&
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• 92(%#<&):/&/0%&4WA#;:%+&)N&/0%&)(,$,-#;&<,+/(,O:=)-&#+&%A%-;G&#+&2)++,O;%&,-&/0%&-%.&<,+/(,O:=)-P&
• b%V-,=)-&)N&*:":;#=A%Y&
>,+/)$(#"&EF:#;,D#=)-&It is possible to use the cumulative distribution function to remap the original distribution as an equally spread distribution simply by looking up each y-value in the original distribution and seeing where it should go in the equalized distribution.
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• 30,W9F:#(%Y&
A high score represents a better match than a low score: • A perfect match is 1; • A maximal mismatch is –1; • A value of 0 indicates no correlation (random association).
A low score represents a better match than a high score. • A perfect match is 0 • A total mismatch is unbounded (depending on the size of the histogram).
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High scores indicate good matches and low scores indicate bad matches. If both histograms are normalized to 1, then: • A perfect match is 1 • A total mismatch is 0
Low scores indicate good matches and high scores indicate bad matches. • A perfect match is 0 • A total mismatch is a 1.
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• 12%-34&0#+&#&<#/#&/G2%&N)(&(%2(%+%-=-$&0,+/)$(#"+&,-&)-%&)(&"#-G&<,"%-+,)-+P&
• !/&,+&%F:,22%<&.,/0&#&A#(,%/G&)N&:+%N:;&N:-*=)-+&/)&%#+,;G&2%(N)("&*)"")-&)2%(#=)-+&)-&0,+/)$(#"+P&
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• For a uniform histogram, ranges is an array of floating-point value pairs, where the number of value pairs is equal to the number of dimensions.
• For a non-uniform histogram, the pairs used by the uniform histogram are replaced by arrays containing the values by which the non-uniform bins are separated. If there are N bins, then there will be N + 1 entries in each of these subarrays.
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• ?0%&/G2%&*#-&O%&%,/0%(&34f>!9?fIccIUR&.0,*0&,+&:+%<&N)(&":;=<,"%-+,)-#;&0,+/)$(#"+&/)&O%&+/)(%<&:+,-$&/0%&<%-+%&":;=<,"%-+,)-#;&"#/(,H&+/(:*/:(%&X,P%PR&3A5#/CbZR&&
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• For the i-th channel there are 30 bins in a range from 0 to 180, therefore 6 levels of intensity for each bin.
• For the j-th channel there are 32 bins in a range from 0 to 255, therefore 8 levels of intensity for each bin.
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• The argument factor is the cutoff for the threshold.
• The result of thresholding a histogram is that all bins whose value is below the threshold factor are set to 0.
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• The source and destination must be a single-channel, 8-bit images of the same size.
• For color images you will have to separate the channels and process them one by one.&
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• *Ac%*/#-$;%XhZY&– 1-%&)N&/0%&(%*/#-$;% +̀&A%(=*%+&#-<&/0%&)22)+,/%&(%*/#-$;%&A%(/%H&– @,-%&*);)(&XcBdZ&)(&O(,$0/-%++&X$(#G+*#;%&,"#$%Z&
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