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In this paper, a novel method for image brightness correction using a contrast limited adaptive histogram equalization was developed to produce constant image brightness levels between and within images.
This technique not only produces more codewords but also receives more robust measurement results for different fringe image brightness levels compared with Gray code techniques.
We have found that this modified LIDE produces image with brightness level closer to that of input image compared to normal LIDE.
The threshold value is an important parameter that depends on a number of factors, such as image brightness, contrast, level of noise, and even edge direction.
For combinations of pupil sizes and field angles, the attenuation of image brightness reaches levels up to 60%.
We found that for combinations of pupil sizes and field angles the attenuation of image brightness may reach levels of more than 60% causing potential loss of contrast sensitivity, which seems to be clinically relevant from our point of view.
An image of various brightness levels thus yields a picture in which these brightnesses are tonally reversed a negative.
Especially, the levels of image brightness, contrast and noise are all different for these three images.
Figure 9(c) indicates relationship histogram of brightness level in florescence cell image treated by LIPUS induction.
The effect of change of brightness level on the image thresholding was considered a minor factor and hence was ignored in the present work.
The contrast of the resulting image is adjusted to enhance the brightness level of the organism blobs while generally reducing the brightness of background noise.
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