By Peter W. Hawkes (Ed.)
This quantity contains chapters discussing photo enhancement and propagation, and box behaviour in hugely anisotropic media. it really is meant for researchers in optical technological know-how, electric engineering, picture processing and mechanical engineering.
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Additional resources for Advances in Imaging and Electron Physics, Vol. 92
Robust Background Estimation with Rank-Order Statistics. Although smoothing, which has been the subject of Section 111, can be considered as the opposite task of background subtraction, these tasks both need to perform first the estimation of a locally dominant gray value u(x, y) inside a more or less large observation window. For smoothing purposes, the window size tends to be smaller than for background compensation, where the window size may coincide with the whole image. , an estimation which is not influenced by outliers, is of great importance.
This filter performs an edge-preserving smoothing, as it averages f ( x , y) only with neighbors that are estimated to belong to the same region as (x, y), since their gray-value differences, with respect to f ( x , y), do not exceed a given threshold. ,A4 are the rank-ordered gray values of V . The subsequent filtering steps are iterations, in successive passes of a median filter performed upon those gray valuesf(i,j) of V that meet the following condition: U , , + ~ ( X , Y )= medianIf(i,j)l: [W)E VI A [ I f ( i , j )- U,(X,Y)~c A = 20, where 0, is the variance in V .
Adaptive Contrast Enhancement in the Neighborhood of Edges In the approach of Beghdadi and Le Negrate (1989), a particular importance is attributed to the contrast enhancement in the neighborhood of edges. Thus, it is a locally computed edge value E that controls the amount of contrast enhancement. The local contrast C, which has to be eventually enhanced, is a measure of the deviation between E and the current gray value f ( x , y ) . First, a transformed (eventually enhanced) contrast value C' is computed.
Advances in Imaging and Electron Physics, Vol. 92 by Peter W. Hawkes (Ed.)