1 CORRELATE Correlation image of two input images or data cubes CORRELATE Computes correlation of two images or data cubes. The result is an im- age (data cube) containing Out(i,j) = < In1(k-i,l-j)*In2(k,l) > averaged over k,l For mode correlation (MODE\$ = YES) or Out(i,j) = - < In1(k-i,l-j)**2 + In2(k,l)**2 - 2 * In1(k-i,l-j)*In2(k,l) > averaged over k,l For mode square (MODE\$ = NO). The correlation is higher when Out(i,j) is near 0. With the minus sign, this means that maximum values indicate highest correlations. Actually, linear conversion formulas are used to keep the correlation image meaningful in user coordinates. The input images must match. When used for example to recenter images, the position of the maximum of the correlation image yields the required recentering. MODE\$ YES (Corre- lation) is to be used when the input distribution has a finite extent, while MODE\$ NO (Square) can be used in any case, but is somewhat slower of course. 2 IN_NAME1\$ TASK\FILE "First input map" IN_NAME1\$ This is the name of the first input map. 2 IN_NAME2\$ TASK\FILE "Second input map" IN_NAME2\$ This is the name of the second input map. 2 OUT_NAME\$ TASK\FILE "Output map" OUT_NAME\$ This is the name of the output map. 2 OUT_SIZE\$ TASK\INTEGER "Number of pixels in the correlation" OUT_SIZE\$[2] Number of pixels (i,j) to keep in the correlation. If set to 0,0, the complete correlation image is computed, otherwise only the specified portion (around the center 0,0) is computed. 2 MODE\$ TASK\LOGICAL "Mode CORRELATION (answer YES) or SQUARE (answer NO)" MODE\$ Select the correlation mode : simple correlation (YES) or least-square distribution (NO). 1 ENDOFHELP