Image restoration by Gauss LU decomposition

It is demonstrated that the Gauss LU decomposition method compares favorably with other existing methods as a powerful tool for the solution of image restoration problems. A computer simulation example, using a spatially separable point spread function, is given.Peer reviewed: YesNRC publication: Ye

Digital image restoration using quadratic programming

The problem of digital image restoration is considered by obtaining an approximate solution to the Fredholm integral equation of the first kind in two variables. The system of linear equations resulting from the discretization of the integral equation is converted to a consistent system of linear equations. The problem is then solved as a quadratic programming problem with bounded variables where the unknown solution is minimized in the L2 norm. In this method minimum computer storage is needed, and the repeated solutions are obtained in an efficient way. Also the rank of the consistent system which gives a best or near best solution is estimated. Computer simulated examples using spatially separable pointspread functions are presented. Comments and conclusion are given.Peer reviewed: YesNRC publication: Ye

Image restoration for space invariant pointspread functions

We show how to apply a truncated eigensystem expansion in the solution of image restoration problems for the case of space invariant point spread functions. The solution is obtained directly from the system of linear equations, which result from the discretization of the Fredholm integral equation of the first kind. Fast Fourier transform techniques are used in obtaining this solution. A procedure is devised to estimate the rank of the coefficient matrix that gives a best or near best solution. It is demonstrated that this algorithm compares favorably with other existing methods. Numerical results using spatially separable point spread functions are given.Peer reviewed: YesNRC publication: Ye

Cross-Angle Transform for Viewer-Independent Recognition of 3-D Objects

NRC publication: Ye

Direct algorithm for digital image restoration

In this paper we report some experimental results of a direct algorithm for the solution of digital image restoration problems. The solution is obtained directly from the system of linear equations that result from the discretization of the Fredholm integral equation of the first kind. This algorithm uses a simple regularized least-squares technique. Also, the regularization parameter for the optimum solution is calculated by a direct (noniterative) method. A computer simulated example using both space invariant and space variant spatially separable point spread functions is presented. We show that this method compares favorably with other known direct methods.Peer reviewed: YesNRC publication: Ye

Computer vision and shape recognition

ix, 451 p. : ill. ; 23 cm

Computer vision and shape recognition

ix, 451 p. : ill. ; 23 cm