Visual Information Processing XXI, Proceedings of SPIE Vol. 8399
Visual Information Processing XXI: SPIE Defense, Security, and Sensing, April 23-27, 2012, Baltimore, Maryland
Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. The reconstructed image suffers from degradations such as blur, aliasing, photo-detector noise and registration and fusion error. Wiener filter can be used to remove artifacts and enhance the visual quality of the reconstructed images. In this paper, we introduce a new fast stochastic Wiener filter for SR reconstruction and restoration that can be implemented efficiently in the frequency domain. Our derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering and image-display processes. We incorporate a new parameter that accounts for LR images registration and fusion errors. Also, we speeded up the performance of the filter by constraining it to work on small patches of the images. Beside this, we introduce two figures of merits: information rate and maximum realizable fidelity, which can be used to assess the visual quality of the resultant images. Simulations and experimental results demonstrate that the derived Wiener filter that can be implemented efficiently in the frequency domain can reduce aliasing, blurring, and noise and result in a sharper reconstructed image. Also, Quantitative assessment using the proposed figures coincides with the visual qualitative assessment. Finally, we evaluate our filter against other SR techniques and its results were very competitive.
Copyright 2012 Society of Photo‑Optical Instrumentation Engineers (SPIE).
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Original Publication Citation
Yousef, A. H., Li, J., & Karim, M. (2012). Fast stochastic Wiener filter for superresolution image restoration with information theoretic visual quality assessment. In M. A. Neifeld & A. Ashok (Eds.), Visual Information Processing XXI, Proceedings of SPIE Vol. 8399 (839906). SPIE of Bellingham, WA. https://doi.org/10.1117/12.918938
Yousef, Amr Hussein; Li, Jiang; Karim, Mohammad; Neifeld, Mark Allen (Ed.); and Ashok, Amit (Ed.), "Fast Stochastic Wiener Filter for Super-Resolution Image Restoration with Information Theoretic Visual Quality Assessment" (2012). Electrical & Computer Engineering Faculty Publications. 398.