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Improving a Single Down-Sampled Image Using Probability-Filtering-Based Interpolation and Improved Poisson Maximum A Posteriori Super-Resolution
EURASIP Journal on Advances in Signal Processing volume 2006, Article number: 097492 (2006)
We present a novel hybrid scheme called "hyper-resolution" that integrates image probability-filtering-based interpolation and improved Poisson maximum a posteriori (MAP) super-resolution to respectively enhance high spatial and spatial-frequency resolutions of a single down-sampled image. A new approach to interpolation is proposed for simultaneous image interpolation and smoothing by exploiting the probability filter coupled with a pyramidal decomposition and the Poisson MAP super-resolution is improved with the techniques of edge maps and pseudo-blurring. Simulation results demonstrate that this hyper-resolution scheme substantially improves the quality of a single gray-level, color, or noisy image, respectively.
Chan RH, Chan TF, Shen L, Shen Z: Wavelet algorithms for high-resolution image reconstruction. SIAM Journal on Scientific Computing 2003, 24(4):1408–1432. 10.1137/S1064827500383123
Schultz RR, Stevenson RL: Extraction of high-resolution frames from video sequences. IEEE Transactions on Image Processing 1996, 5(6):996–1011. 10.1109/83.503915
Elad M, Feuer R: Super-resolution reconstruction of image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence 1999, 21(9):817–834. 10.1109/34.790425
Hardie RC, Barnard KJ, Armstrong EE: Joint MAP registration and high-resolution image estimation using a sequence of undersampled images. IEEE Transactions on Image Processing 1997, 6(12):1621–1633. 10.1109/83.650116
Liu C, Shum H-Y, Zhang C-S: A two-step approach to hallucinating faces: global parametric model and local nonparametric model. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '01), December 2001, Kauai, Hawaii, USA 1: I-192–I-198.
Baker S, Kanade T: Limits on super-resolution and how to break them. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '00), June 2000, Hilton Head Island, SC, USA 2: 372–379.
Hou H, Andrews H: Cubic splines for image interpolation and digital filtering. IEEE Transactions on Acoustics, Speech, and Signal Processing 1978, 26(6):508–517. 10.1109/TASSP.1978.1163154
Jain AK: Fundamentals of Digital image Processing. Prentice-Hall, Englewood Cliffs, NJ, USA; 1989.
Keys R: Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics, Speech, and Signal Processing 1981, 29(6):1153–1160. 10.1109/TASSP.1981.1163711
Hong KP, Paik JK, Kim HJ, Lee CH: An edge-preserving image interpolation system for a digital camcorder. IEEE Transactions on Consumer Electronics 1996, 42(3):279–284. 10.1109/30.536121
Gurski GC, Orchard MT, Hull AW: Optimal linear filters for pyramidal decomposition. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '92), March 1992, San Francisco, Calif, USA 4: 633–636.
Ramstad T, Wang Y, Mitra SK: Efficient image interpolation scheme using hybrid IIR Nyquist filters. Optical Engineering 1992, 31(6):1277–1283. 10.1117/12.56181
Carrato S, Ramponi G, Marsi S: A simple edge-sensitive image interpolation filter. Proceedings of International Conference on Image Processing (ICIP '96), September 1996, Lausanne, Switzerland 3: 711–714.
Li X, Orchard MT: New edge directed interpolation. Proceedings of International Conference on Image Processing (ICIP '00), September 2000, Vancouver, British Columbia, Canada 2: 311–314.
Ayazifar B, Lim JS: PEL-adaptive model-based interpolation of spatially subsampled images. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '92), March 1992, San Francisco, Calif, USA 3: 181–184.
Hunt BR, Sementilli PJ: Description of a Poisson imagery super-resolution algorithm. In Astronomical Data Analysis Software and System I. Volume 25. Edited by: Worrall DM, Biemserfer C, Barnes J. Astronomical Society of the Pacific, San Francisco, Calif, USA; 1992:196–199.
Sementilli PJ, Nadar MS, Hunt BR: Poisson MAP super-resolution estimator with smoothness constraint. Neural and Stochastic Methods in Image and Signal Processing II, July 1993, San Diego, Calif, USA, Proceedings of SPIE 2032: 2–13.
Lucy LB: An iterative technique for the rectification of observed distributions. The Astronomical Journal 1974, 79(6):745–765.
Richardson WH: Bayesian-based iterative method of image restoration. Journal of the Optical Society of America 1972, 62(1):55–59. 10.1364/JOSA.62.000055
Frieden BR: Restoring with maximum likelihood and maximum entropy. Journal of the Optical Society of America 1972, 62(4):511–518. 10.1364/JOSA.62.000511
Sezan MI, Tekalp AM: Iterative image restoration with ringing suppression using themethod of POCS. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '88), April 1988, New York, NY, USA 2: 1300–1303.
Pan M-C, Lettington AH: Smoothing images by a probability filter. Proceedings of IEEE International Joint Symposia on Intelligence and Systems (IJSIS '98), May 1998, Rockville, Md, USA 343–346.
Pan M-C: A novel blind super-resolution technique based on the improved Poisson maximum a posteriori algorithm. International Journal of Imaging Systems and Technology 2002, 12(6):239–246. 10.1002/ima.10032
Unser M, Aldroubi A, Eden M: B-spline signal processing. I. Theory. IEEE Transactions on Signal Processing 1993, 41(2):821–833. 10.1109/78.193220
Lee C, Eden M, Unser M: High-quality image resizing using oblique projection operators. IEEE Transactions on Image Processing 1998, 7(5):679–692. 10.1109/83.668025
Unser M: Splines: a perfect fit for signal and image processing. IEEE Signal Processing Magazine 1999, 16(6):22–38. 10.1109/79.799930
Kimmel R: Demosaicing: image reconstruction from color CCD samples. IEEE Transactions on Image Processing 1999, 8(9):1221–1228. 10.1109/83.784434
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Pan, M. Improving a Single Down-Sampled Image Using Probability-Filtering-Based Interpolation and Improved Poisson Maximum A Posteriori Super-Resolution. EURASIP J. Adv. Signal Process. 2006, 097492 (2006) doi:10.1155/ASP/2006/97492
- Information Technology
- Quantum Information
- Noisy Image
- Hybrid Scheme