文件名称:localnormalizematlab
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Stretches contrast on the image and normalize image from 0 to 1
The main difference of this function to the standard streching functions is that
standard function finds global minimum and maximum on the image, then uses
some low and high threshold values to normalize image(values below LowTHR are
equated to LowTHR and values above HighTHR are equated to HighTHR). This function
uses threshold values that are NEXT to miminum and maximum. Thus, we can exclude
image backgound (which is normally zero) and find minimum value on the image itself.
Same consideration goes to high thr. We exclude first global maximum because, if its
a spike, we have better chance with the next value, and if it is not a spike, normally,
next value is quite close to max (assuming smooth image), so our error is sma- Stretches contrast on the image and normalize image from 0 to 1
The main difference of this function to the standard streching functions is that
standard function finds global minimum and maximum on the image, then uses
some low and high threshold values to normalize image(values below LowTHR are
equated to LowTHR and values above HighTHR are equated to HighTHR). This function
uses threshold values that are NEXT to miminum and maximum. Thus, we can exclude
image backgound (which is normally zero) and find minimum value on the image itself.
Same consideration goes to high thr. We exclude first global maximum because, if its
a spike, we have better chance with the next value, and if it is not a spike, normally,
next value is quite close to max (assuming smooth image), so our error is small
The main difference of this function to the standard streching functions is that
standard function finds global minimum and maximum on the image, then uses
some low and high threshold values to normalize image(values below LowTHR are
equated to LowTHR and values above HighTHR are equated to HighTHR). This function
uses threshold values that are NEXT to miminum and maximum. Thus, we can exclude
image backgound (which is normally zero) and find minimum value on the image itself.
Same consideration goes to high thr. We exclude first global maximum because, if its
a spike, we have better chance with the next value, and if it is not a spike, normally,
next value is quite close to max (assuming smooth image), so our error is sma- Stretches contrast on the image and normalize image from 0 to 1
The main difference of this function to the standard streching functions is that
standard function finds global minimum and maximum on the image, then uses
some low and high threshold values to normalize image(values below LowTHR are
equated to LowTHR and values above HighTHR are equated to HighTHR). This function
uses threshold values that are NEXT to miminum and maximum. Thus, we can exclude
image backgound (which is normally zero) and find minimum value on the image itself.
Same consideration goes to high thr. We exclude first global maximum because, if its
a spike, we have better chance with the next value, and if it is not a spike, normally,
next value is quite close to max (assuming smooth image), so our error is small
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下载文件列表
README.txt
testlocalnormalize.m
localnormalize.m
testlocalnormalize.m
localnormalize.m