Zala, C ABarrodale, ILucas, C EMacKinnon, R F2009-07-162009-07-1619891989Zala, C., et al, PACRIM.1989, p. 87-90http://hdl.handle.net/1828/1462©1989 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.A formulation of the maximum entropy (ME) method is described, where the data constraints are expressed in the form of fixed bounds on the elements of an orthogonal transform of the model. The bounds are set on the basis of both the observed data and an estimate of the noise statistics in the transform domain; prior knowledge, if available, can also be incorporated. Using a special-purpose conjugate gradient algorithm developed for this problem, one-dimensional examples are presented that illustrate substantial SNR enhancement using the new formulation with both Fourier and Walsh transforms. A simple strategy for selecting an initial feasible solution for the algorithm is presented.enconjugate gradient algorithmdata constraintsFourier transformsimage processingmaximum entropy methodnoise statisticsobserved dataorthogonal transformpicture processingSNR enhancementtransform domain constraintsWalsh transformsOtherDepartment of Computer Science