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The main reason that the best method is different in each database is because each database is different from the others, in terms of lighting, image quality, zoom, and camera perspective.
According to Eq. (12), the weight v k, j) between two pixels (x k, y k ) and (x j, y j ) in the original even lighting image f is: vleft k,jright)=frac{exp left -{leftVert {N}_k-{N}_jrightVert}_{2,a}^2/{h}^2right)}{sum left -{leftVert_k^r}{N}_k-{N}_jrightVert {N}_{2{N}_jrightVert}_{sum}^2right)/{h}^2}}.
According to Eq. (11), the estimated value ( overline{Q}left({x}_k,{y}_kright) ) of the pixel (x k, y k ) in the original even lighting image f is computed as: overline{Q}left({x}_k,{y}_kright)=sum limits_{left({x}_j,{y}_jright)in {V}_k^r}vleft k,jright)Qleft({x}_j,{y}_jright).
Similarly, if (g(T s ) + g(P s ))/2 < g(k) ≤ g(P s ), the membership degree of the pixel k in the original even lighting image f according to the S-function in Eq. (14) is mu left(g k)right)=1-2{left(frac{g k -gleft {P}_sright)}{gleft {P}_sright -gleft {T}{gleft {P}_sright -gleft {
If g(T s ) ≤ g(k) ≤ (g(T s ) + g(P s ))/2, the membership degree (the wave transformation value) of the pixel k in the original even lighting image f according to the S-function in Eq. (14) is mu left(g k)right)=2{left(frac{g k -gleft {T}_sright)}{glefrac{g k -gleft {efT}_srightght)}{gleft {P}_sright -gleft {
Variation in lighting, image resolution, pose, and occlusions has only been restricted when it obscures the facial characteristics (such as a hand covering the face).
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Because it's based on contrast, Seddon says that the system performs well when dealing with poorly lit images.
Drag the lightness slider to the right for a lighter image.
(a) White light image, (b) LSF image and (c) LSF image with rank filter applied.
Images were blended, then superimposed on an incident white light image of the sample taken using a Leica M165C microscope.
d Reflected light image.
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