DESIGN OF SYNTHETIC ESTIMATION FILTERS USING CORRELATION-ENERGY MINIMIZATION

Synthetic estimation filters (SEFs) have been found useful for the det ermination of distortion parameters such as angle of rotation of objec ts from their images. Previous SEFs, designed using matched and phase- only filters required a knowledge of the exact location of the object to produce reasonable estimation accuracy. To overcome the limitation, use of minimum average correlation energy (MACE) filters is proposed for the construction of SEFs. Because the MACE filters are designed to have their peaks at the origin of the correlation plane, the peak can be detected without a knowledge of the exact position of the object. Computer simulations are used to study the performance of MACE-SEFs. I t is found that significant errors result at rotation angles that are not part of the training set. An improved linearity leading to an incr ease in accuracy was realized when the minimum noise correlation energ y (MINACE) concept was used in place of the MACE concept for the desig n of the SEFs.