Degrees of freedom for projection imaging

This paper presents the use of the gramian as an aid in defining the degrees of freedom (DOF) in projection imaging systems. The gramian is developed for a general continuous-discrete imaging model and is then applied to the specific case of projection imaging. The theoretical development shows the general structure of the gramian to be quite well behaved and indicates where redundant data are achieved and the best ways of increasing the degrees of freedom with a minimum sample increase. The experimental development shows these inherent limitations on gramians up to 32 768 by 32 768 and is experimentally confirmed by reconstructing a series of projection images.

[1]  Rangasami L. Kashyap,et al.  Picture Reconstruction from Projections , 1975, IEEE Transactions on Computers.

[2]  F. Gori,et al.  Shannon number and degrees of freedom of an image , 1973 .

[3]  G. Herman,et al.  Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and x-ray photography. , 1970, Journal of theoretical biology.

[4]  Harry C. Andrews,et al.  Fundamental Limits And Degrees Of Freedom Of Imaging Systems , 1976, Other Conferences.

[5]  B. R. Hunt,et al.  The Application of Constrained Least Squares Estimation to Image Restoration by Digital Computer , 1973, IEEE Transactions on Computers.

[6]  H. Andrews,et al.  Singular value decompositions and digital image processing , 1976 .

[7]  A. KLUG,et al.  Three-dimensional Image Reconstruction from the Viewpoint of information Theory , 1972, Nature.

[8]  D. Slepian Prolate spheroidal wave functions, Fourier analysis and uncertainty — IV: Extensions to many dimensions; generalized prolate spheroidal functions , 1964 .

[9]  A. C. Riddle,et al.  Inversion of Fan-Beam Scans in Radio Astronomy , 1967 .

[10]  Richard Bellman,et al.  Introduction to Matrix Analysis , 1972 .

[11]  D. DeRosier,et al.  The reconstruction of a three-dimensional structure from projections and its application to electron microscopy , 1970, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[12]  B. Hunt A matrix theory proof of the discrete convolution theorem , 1971 .

[13]  S Twomey Information content in remote sensing. , 1974, Applied optics.

[14]  S. Twomey The application of numerical filtering to the solution of integral equations encountered in indirect sensing measurements , 1965 .

[15]  Terry M. Peters,et al.  Image reconstruction from finite numbers of projections , 1973 .

[16]  R. Bracewell Strip Integration in Radio Astronomy , 1956 .

[17]  G. N. Ramachandran,et al.  Three-dimensional reconstruction from radiographs and electron micrographs: application of convolutions instead of Fourier transforms. , 1971, Proceedings of the National Academy of Sciences of the United States of America.