Super-resolution in practice: The complete pipeline from image capture to super-resolved subimage creation using a novel frame selection method

Machine Vision and Applications

Volumn 23, Issue 3, 2012, Pages 441-459

  Petrou, Maria ^a   Jaward, Mohamed H ^a   Chen, Shengyong ^a   Briers, Mark ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b QINETIQ   (United Kingdom)

Author keywords

Frame selection; Image quality assessment; Super resolution

Indexed keywords

FRAME QUALITY; FRAME SELECTION; IMAGE CAPTURES; IMAGE QUALITY ASSESSMENT; PRACTICAL SYSTEMS; REGION OF INTEREST; REGIONS OF INTEREST; REGISTRATION ALGORITHMS; STATE OF THE ART; SUB PIXELS; SUBIMAGES; SUPER RESOLUTION; SUPER RESOLUTION ALGORITHMS; VIBRATING PLATFORM;

ALGORITHMS; CAMERAS; IMAGE QUALITY;

OPTICAL RESOLVING POWER;

EID: 84861678824     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-010-0315-7     Document Type: Article

References (33)

1. Baboulaz, L., Dragotti, P.L.: Exact feature extraction using finite rate of innovation principles with an application to image superresolution. IEEE Trans. Image Process. 18(2), 281-298 (2009)
2. Bascle, B., Blake, A., Zisserman, A.: Motion deblurring and superresolution from an image sequence. In: European Conference on Computer Vision. Lecture Notes in Computer Science, vol. 1065, pp 571-582 (1996)
3. Black, M., Anandan, P.: The robust estimation ofmultiplemotions: Parametric and piecewise-smooth flow fields. Comput. Vis. Image Understand. 63(1), 75-104 (1996)
4. Blake, A., Zisserman, A.: Visual Reconstruction. MIT Press, Cambridge (1987)
5. Domke, J., Aloimonos, Y.: Image transformations and blurring. IEEETrans. Pattern Anal.Mach. Intell. 31(5), 811-823 (2009)
6. Esparragon, D.R., Gonzalez, L.M.M., Santana, J.G.V., Ortiz, J.C.: Automatic image quality measurement tool. In: 3rd International Conference on Information and Communication Technologies: From Theory to Applications, pp. 1-6, April (2008)
7. Ferzli, R., Karam, L.J.: A No-reference objective image sharpness metric based on the notion of just noticeable blur (JNB). IEEE Trans. Image Process. 18(4), 717-728 (2009)
8. Gunawan, I.P., Ghanbari, M.: Reduced-reference video quality assessment using discriminative local harmonic strength with motion consideration. IEEE Trans. Circ. Syst. Video Technol. 18(1), 71-83 (2008)
9. Hardie, R., Barnard, K., Armstrong, E.: Joint MAP registration and high-resolution image estimation using a sequence of undersampled images. IEEE Trans. Image Process. 6(2), 1621-1633 (1997)
10. Katartzis, A., Petrou, M.: Robust Bayesian estimation and normalised convolution for super-resolution image reconstruction. In: Workshop on Image Registration and Fusion, ComputerVision and Pattern Recognition, CVPR'07, Minneapolis, USA, 18-23 June 2007, pp. 1-7 (2007)
11. Katartzis, A., Petrou, M.: Current trends in super-resolution image reconstruction. In: Stathaki, T. (ed.) Image Fusion: Algorithms and Applications, Academic Press, New York (2008)
12. Knutsson, H., Westin, C.: Normalised and differential convolution. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 93, pp. 515-523 (1993)
13. Lee, W.-H., Lai, S.-H., Chen, C.-L.: Iterative blind image motion deblurring via learning a No-reference image quality measure. IEEE Int. Conf. Image Process. 4, 405-408 (2007)
14. Li, B., Osberger, W.: Measurement of blurring in video sequences, United States Patent 7099518 (2006)
15. Mei, T., Hua, X.-S., Zhu, C.-Z., Zhou, H.-Q., Li, S.: Home video visual quality assessment with spatiotemporal factors. IEEE Trans. Circ. Syst. Video Technol. 17(6), 699-706 (2007)
16. Nguyen, N., Milanfar, P., Golub, G.: Efficient generalised crossvalidation with applications to parametric image restoration and resolution enhancement. IEEE Trans. Image Process. 10(9), 308-1299 (2001)
17. Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction. IEEE Signal Process. Mag. 20(3), 21-36 (2003)
18. Petrou, M., Petrou, C.: Image Processing, the Fundamentals, J Wiley. ISBN: 9780470745861 (2010)
19. Pham, T., van Vliet, L., Schutte, K.: Robust fusion of irregularly sampled data using adaptive normalised convolution. EURASIP J. Appl. Signal Process. pp. 1-12 (2006)
20. Ponomarenko, N., Battisti, F., Egiazarian, K., Astola, J., Lukin, V.: Metrics performance comparison for colour image databases. In: Fourth International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, Arizona, USA. January 14-16 (2009)
21. Robinson, D., Milanfer, P.: Fundamental performance limits in image registration. IEEE Trans. Image Process. 13(9), 1185-1199 (2004)
22. Segall, C., Katsaggelos, A., Molina, R., Mateos, J.: Bayesian resolution of enhancement of compressed video. IEEE Trans. Image Process. 13(7), 898-910 (2004)
23. Sheikh, H.R., Bovik, A.C., Cormack, L.: No-reference quality assessment using natural scene statistics: JPEG2000. IEEE Trans. Image Process. 14(11), 1918-1927 (2005)
24. Sheikh, H.R., Bovik, A.C.: Image information and visual quality. IEEE Trans. Image Process. 15(2), 430-444 (2006)
25. Shen, H., Ng, M.K., Li, P., Zhang, L.: Super-resolution reconstruction algorithm toMODIS remote sensing images.Comput J. doi:10. 1093/compjnl/bxm028 (2007)
26. Shen, H., Zhang, L., Huang, B., Li, P.: A MAP approach for joint motion estimation, segmentation and super resolution. IEEE Trans. Image Process. 16(2), 479-490 (2007)
27. Shnayderman, A., Gusev, A., Eskicioglu, A.M.: An SVD-based gray scale image quality measure for local and global assessment. IEEE Trans. Image Process. 15(2), 422-429 (2006)
28. Thevenaz, P., Ruttimann, U., Unser, M.: A pyramid approach to subpixel registration based on intensity. IEEE Trans. Image Process. 7(1), 27-41 (1998)
29. Wang, X., Tian, B., Liang, C., Shi, D.: Blind image quality assessment for measuring image blur. Congress Image Sig. Process. CISP' 08(1), 467-470 (2008)
30. Wee, C.-Y., Paramesran, R.: Measure of image sharpness using eigenvalues. Int. J. Inform. Sci. 177(12), 2533-2552 (2007)
31. Woods, N., Galatsanos, N., Katsaggelos, A.: Stochastic methods for joint registration, restoration, and interpolation of multiple undersampled images. IEEE Trans. Image Process. 15(1), 201-213 (2006)
32. Zamani, A.N., Awang, M.K., Omar, N., Nazeer, S.A.: Image quality assessments and restoration for face detection and recognition system images. In: Second Asia International Conference on Modelling and Simulation, pp. 505-510, May (2008)
33. Zheng, H., Hellwich, O.: VQ-based Bayesian Estimation for Blur Identification and Image Selection in Video Sequences. Int. J. Innov. Comput. Inform. Control (IJICIC) 2(2), 399-410 (2006)