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51 %      build an interval tree of zero crossings in the second derivative
863 % DerivativeHistogram() determines the derivative of the histogram using
869 % double *derivative)
876 % o derivative: This array of doubles is initialized by
877 % DerivativeHistogram to the derivative of the histogram using central
882 double *derivative)
892 derivative[0]=(-1.5*histogram[0]+2.0*histogram[1]-0.5*histogram[2]);
893 derivative[n]=(0.5*histogram[n-2]-2.0*histogram[n-1]+1.5*histogram[n]);
895 Compute derivative using central differencing.
898 derivative[i]=(histogram[i+1]-histogram[i-1])/2.0;
931 % derivative of the histogram. As the value is increased, you can expect a
932 % smoother second derivative.
1517 *derivative,
1559 derivative=(double *) AcquireQuantumMemory(256,sizeof(*derivative));
1562 if ((derivative == (double *) NULL) ||
1571 DerivativeHistogram(zero_crossing[i].histogram,derivative);
1572 DerivativeHistogram(derivative,second_derivative);
1583 DerivativeHistogram(zero_crossing[i].histogram,derivative);
1584 DerivativeHistogram(derivative,second_derivative);
1588 derivative=(double *) RelinquishMagickMemory(derivative);
1786 % derivative of the histogram. As the value is increased, you can expect a
1787 % smoother second derivative.
1887 % second derivative of the histogram of a particular color component.
1890 % -1, 0, or 1 representing the slope of the first derivative of the