Download Advances in Imaging and Electron Physics, Vol. 92 by Peter W. Hawkes (Ed.) PDF

By Peter W. Hawkes (Ed.)

This quantity comprises chapters discussing snapshot enhancement and propagation, and box behaviour in hugely anisotropic media. it truly is meant for researchers in optical technology, electric engineering, photograph processing and mechanical engineering.

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Extra info for Advances in Imaging and Electron Physics, Vol. 92

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The background of drawings, manuscripts, and other similar images is in practice not sufficiently uniform. The elimination of this spurious shading can represent a most decisive enhancement of the image quality, especially in view of binarizing the image signal, as shown schematically by Fig. 9. , text, drawings), a binarization with fixed threshold can lead to serious errors in the presence of a pronounced background shading. , of the lowest possible spatial frequency, it can be extracted from the image signal f ( x , y ) by means of a spatial low-pass filter with a properly chosen cutoff frequency.

Anisotropy-Controlled Adaptive Extremum Sharpening Filter A local degree of anisotropy a can be defined axiomatically as a quantity between 0, for a perfectly isotropic window (a gray-value terrace), and 1 , for a maximally anisotropic pattern, as for instance for a one-pixel thin straight line. , UT represented in Fig. 16, where T = 4 in Fig. 16a, and T = 2(L - 1) = 12 45 IMAGE ENHANCEMENT in Fig. , T , be the average gray value in CJ,. The with Max = max ( p t ) ,Min t = I ... r = min ( p t ) , t= 1 ...

Figure 10 shows at the upper left the watermark of an ancient manuscript, and at the lower left the background obtained with L = 32. The discontinuities at the field borders of the background image can be smoothed with a fast small-window (21 x 21 in this case) separable averaging filter before performing the image subtraction, whose result is displayed at the lower right of the same figure. Subtracting a background function, as described earlier, which substantially spans the same gray-value range as the original gray-value function may cause too strong an enhancement of the high spatial frequencies, contained in the differencef(x, y ) - k * g(x, y ) , if k is chosen too near to 1.

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