5.3.1 Image Restoration -- General, Survey, Evaluations

Chapter Contents (Back)
Restoration. Survey, Restoration. See also Image Quality Evaluation, Visual Quality, Quality Assessment, and Imaging Models.

Harris, J.L.,
Image Evaluation and Restoration,
JOSA(56), No. 5, May 1966, pp. 569-574. BibRef 6605

Rushforth, C.K., Harris, R.W.,
Restoration, Resolution, and Noise,
JOSA(58), No. 4, April 1968, pp. 539-545. BibRef 6804

Trussell, H.J., Civanlar, M.R.,
The Feasible Solution in Signal Restoration,
ASSP(32), No. 2, 1984, pp. 201-212. Constraints described as convex sets. BibRef 8400

Sezan, M.I., Tekalp, A.M., (Eds.)
Image Restoration and Reconstruction,
OptEng(29), No. 5, May 1990, pp. 391-574. Special issue. BibRef 9005

Sezan, M.I., Stark, H.,
Image restoration by the method of convex projections: Part 2,
MedImg(1), October 1982, pp. xx-yy. BibRef 8210

Sezan, M.I., Tekalp, A.M.,
Survey of recent developments in digital image restoration,
OptEng(29), No. 5, May 1990, pp. 393-404. Survey, Restoration. In the Special issue. BibRef 9005

Katsaggelos, A.K., Mammone, R.J., (Eds.)
Special Issue: Image Restoration,
JVCIR(3), No. 4, December 1992, pp. 305-455. BibRef 9212

Katsaggelos, A.K.,
Digital Image Restoration (Book),
SpringerBerlin, 1991. BibRef 9100

Banham, M.R., Katsaggelos, A.K.,
Digital Image Restoration,
SPMag(14), No. 2, March 1997, pp. 24-41. 9704
BibRef

Hong, M.C., Stathaki, T., and Katsaggelos, A.K.,
A Mixed Norm Image Restoration,
ICIP97(I: 385-388).
IEEE DOI BibRef 9700

May, K., Stathaki, T., Constantinides, A.G., Katsaggelos, A.K.,
Iterative determination of local bound constraints in iterative image restoration,
ICIP98(II: 833-837).
IEEE DOI 9810
BibRef

Hong, M.C.[Min-Cheol], Stathaki, T.,
A regularized least mean mixed norm multichannel image restoration algorithm,
ICIP98(II: 828-832).
IEEE DOI 9810
BibRef

Reeves, S.J., Mersereau, R.M.,
Automatic assessment of constraint sets in image restoration,
IP(1), No. 1, January 1992, pp. 119-123.
IEEE DOI 0402
BibRef

Reeves, S.J.,
Optimal space-varying regularization in iterative image restoration,
IP(3), No. 3, May 1994, pp. 319-324.
IEEE DOI 0402
BibRef

Reeves, S.J.,
Fast image restoration without boundary artifacts,
IP(14), No. 10, October 2005, pp. 1448-1453.
IEEE DOI 0510
BibRef

King, I.R.,
Some Practical Aspects of Image Restoration,
IJIST(6), No. 4, Winter 1995, pp. 392-394. BibRef 9500

Choy, S.S.O., Chan, Y.H.[Yuk-Hee], Siu, W.C.[Wan-Chi],
New Image Restoration Performance-Measures with High-Precision,
OptEng(36), No. 4, April 1997, pp. 1035-1043. 9705
BibRef
Earlier:
New adaptive iterative image restoration algorithm,
ICIP94(II: 670-674).
IEEE DOI 9411
BibRef

Fienup, J.R.,
Invariant Error Metrics for Image Reconstruction,
AppOpt(36), No. 32, November 10 1997, pp. 8352-8357. 9711
BibRef

Thurman, S.T.[Samuel T.], Fienup, J.R.[James R.],
Noise histogram regularization for iterative image reconstruction algorithms,
JOSA-A(24), No. 3, March 2007, pp. 608-617.
WWW Link. 0801
BibRef

Kuo, S.M., Morgan, D.R.,
Active noise control: a tutorial review,
PIEEE(87), No. 6, June 1999, pp. 943-973.
IEEE DOI 9906
Survey, Noise. BibRef

Uma, S., Annadurai, S.,
A Review: Restoration Approaches,
GVIP(05), No. V8, 2005, pp. 23-35.
HTML Version. BibRef 0500

Hasegawa, Y.[Yasumichi],
Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images,
Springer-Verlag2009. ISBN: 978-3-642-03216-5
WWW Link. Buy this book: Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images (Lecture Notes in Electrical Engineering) 0910
BibRef

Chatterjee, P., Milanfar, P.[Peyman],
Is Denoising Dead?,
IP(19), No. 4, April 2010, pp. 895-911.
IEEE DOI 1003
Evaluation, Denoising. Since recent work seems to be about as good as the past, is there a theoretical limit and are we there yet? Conclusion, not at the limit yet. BibRef

Chatterjee, P., Milanfar, P.[Peyman],
Practical Bounds on Image Denoising: From Estimation to Information,
IP(20), No. 5, May 2011, pp. 1221-1233.
IEEE DOI 1104
See also Patch-Based Near-Optimal Image Denoising. BibRef

Russo, F.,
New Method for Performance Evaluation of Grayscale Image Denoising Filters,
SPLetters(17), No. 5, May 2010, pp. 417-420.
IEEE DOI 1003
BibRef

Chickerur, S.[Satyadhyan], Kumar M., A.[Aswatha],
Image Restoration: Past, Present and Future,
RPCS(3), No. 3 2010, pp. 108-126.
WWW Link. 1003
BibRef

Jouini, W.,
Energy Detection Limits Under Log-Normal Approximated Noise Uncertainty,
SPLetters(18), No. 7, July 2011, pp. 423-426.
IEEE DOI 1101
BibRef

Pavithra, S., Narasimhan, S.V.,
Feedback active noise control based on forward-backward LMS predictor,
SIViP(7), No. 6, November 2013, pp. 1083-1091.
Springer DOI 1310
Noise cancellation. BibRef

Pavithra, S., Narasimhan, S.V.,
Feedback active noise control based on transform-domain forward-backward LMS predictor,
SIViP(8), No. 3, March 2014, pp. 479-487.
WWW Link. 1403
BibRef

Shao, L., Yan, R., Li, X., Liu, Y.,
From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms,
Cyber(44), No. 7, July 2014, pp. 1001-1013.
IEEE DOI 1407
Survey, Denoising. Dictionaries BibRef


Akkoul, S.[Smaïl], Ledee, R.[Roger], Leconge, R.[Remy], Leger, C.[Christophe], Harba, R.[Rachid], Pesnel, S.[Sabrina], Lerondel, S.[Stéphanie], Lepape, A.[Alain], Vilcahuaman, L.[Luis],
Comparison of Image Restoration Methods for Bioluminescence Imaging,
ICISP08(163-172).
Springer DOI 0807
BibRef

Kokaram, A.[Anil],
Ten Years of Digital Visual Restoration Systems,
ICIP07(IV: 1-4).
IEEE DOI 0709
BibRef

Kornprobst, P., Deriche, R., Gilles, A.,
Nonlinear Operators in Image Restoration,
CVPR97(325-330).
IEEE DOI 9704
Halfquadratic minimization is best.
PS File. BibRef

Ferreira, P.J.S.G.,
The stability of certain image restoration problems: Quantitative results,
ICIP95(II: 29-32).
IEEE DOI 9510
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Restoration: Filter Approaches .


Last update:Mar 13, 2017 at 16:25:24