Abstract

It is suggested that passive-camera range-sensing methods be considered as returning not just range values but rather probability density functions, characterized by two-dimensional arrays of both expected value and variance. Employing variance data permits probabilistic integration of the range values from multiple range-sensing algorithms, with results demonstrably superior to simple averaging. This method is analyzed and carried out for sign-bit correlation stereopsis and two-lens depth-from-focus. Calculating the Cramér–Rao lower bound on variance for these two range-sensing algorithms can be done with relatively little additional computation.

© 1990 Optical Society of America

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