Discrete cosine transform based regularized high-resolution image reconstruction algorithm
- 1 August 1999
- journal article
- Published by SPIE-Intl Soc Optical Eng in Optical Engineering
- Vol. 38 (8), 1348-1356
- https://doi.org/10.1117/1.602177
Abstract
While high-resolution images are required for various applications, aliased low-resolution images are only available due to the physical limitations of sensors. We propose an algorithm to reconstruct a high-resolution image from multiple aliased low-resolution images, which is based on the generalized deconvolution technique. The conventional approaches are based on the discrete Fourier transform (DFT) since the aliasing effect is easily analyzed in the frequency domain. However, the useful solution may not be available in many cases, i.e., the underdetermined cases or the insufficient subpixel information cases. To compensate for such ill-posedness, the generalized regularization is adopted in the spatial domain. Furthermore, the usage of the discrete cosine transform (DCT) instead of the DFT leads to a computationally efficient reconstruction algorithm. The validity of the proposed algorithm is both theoretically and experimentally demonstrated. It is also shown that the artifact caused by inaccurate motion information is reduced by regularization. © 1999 Society of Photo-Optical Instrumentation Engineers.Keywords
This publication has 9 references indexed in Scilit:
- Two approaches for image-processing based high resolution image acquisitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Generalized multichannel image deconvolution approach and its applicationsOptical Engineering, 1998
- Simultaneous multichannel image restoration and estimation of the regularization parametersIEEE Transactions on Image Processing, 1997
- General choice of the regularization functional in regularized image restorationIEEE Transactions on Image Processing, 1995
- Subpixel registration for a high resolution imaging scheme using multiple imagersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- High-resolution image reconstruction from lower-resolution image sequences and space-varying image restorationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Improving resolution by image registrationCVGIP: Graphical Models and Image Processing, 1991
- Recursive reconstruction of high resolution image from noisy undersampled multiframesIEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
- High-resolution image recovery from image-plane arrays, using convex projectionsJournal of the Optical Society of America A, 1989