Shape Recovery from Equal Thickness Contours

A unique imaging modality based on equal thickness contours (ETC) has introduced a new opportunity for 3D shape reconstruction from multiple views. These ETC can be generated through an interference between transmitted and diffracted beams. We present a computational framework for representing each view of an object in terms of its object thickness and then integrating these representations into a 3D surface by algebraic reconstruction. In this framework, the object thickness is first derived from ideal contours and then extended to real data. For real data, the object thickness is inferred by grouping curve segments that correspond to points of second derivative maxima. At each step of the process, we use some form of regularization to ensure closeness to the original features as well as neighborhood continuity. We apply our approach to images of a submicron crystal structure obtained through a holographic process.

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

[2]  Bahram Parvin,et al.  Shape from equal thickness contours , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[3]  Lawrence C. Evans Estimates for smooth absolutely minimizing Lipschitz extensions. , 1993 .

[4]  C. Werner,et al.  Satellite radar interferometry: Two-dimensional phase unwrapping , 1988 .

[5]  Hugh Griffiths,et al.  Interferometric synthetic aperture radar , 1995 .

[6]  R. Goldstein,et al.  Mapping small elevation changes over large areas: Differential radar interferometry , 1989 .

[7]  Gianfranco Fornaro,et al.  Robust phase-unwrapping techniques: a comparison , 1996 .

[8]  Gunnar Aronsson,et al.  On certain singular solutions of the partial differential equation ux2uxx+2uxuyuxy+uy2uyy=0 , 1984 .

[9]  Akira Tonomura,et al.  Progress in Holographic Interference Electron Microscopy , 1995 .

[10]  Baba C. Vemuri,et al.  On Three-Dimensional Surface Reconstruction Methods , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  K. Feigl,et al.  The displacement field of the Landers earthquake mapped by radar interferometry , 1993, Nature.

[12]  Thomas Kreis,et al.  Digital holographic interference-phase measurement using the Fourier-transform method , 1986 .

[13]  Jean-Daniel Boissonnat,et al.  Shape reconstruction from planar cross sections , 1988, Comput. Vis. Graph. Image Process..

[14]  Bahram Parvin,et al.  Curve evolution for corner enhancement , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[15]  Didier Massonnet,et al.  SATELLITE RADAR INTERFEROMETRY , 1997 .

[16]  Giorgio Franceschetti,et al.  Global and local phase-unwrapping techniques: a comparison , 1997 .

[17]  H. Takajo,et al.  Least-squares phase estimation from the phase difference , 1988 .

[18]  D. Gabor A New Microscopic Principle , 1948, Nature.

[19]  Ali Mohammad-Djafari,et al.  Reconstruction of the shape of a compact object from few projections , 1997, Proceedings of International Conference on Image Processing.

[20]  Gunnar Aronsson,et al.  On the partial differential equationux2uxx+2uxuyuxy+uy2uyy=0 , 1968 .

[21]  Richard Gordon,et al.  Reconstruction of pictures from their projections , 1971, CACM.

[22]  Philippe Saint-Marc,et al.  Adaptive Smoothing: A General Tool for Early Vision , 1991, IEEE Trans. Pattern Anal. Mach. Intell..