TR2008-089

Sensing Increased Image Resolution Using Aperture Masks


    •  Mohan, A., Huang, X., Tumblin, J., Raskar, R., "Sensing Increased Image Resolution Using Aperture Masks", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), , June 2008, pp. 1-8.
      BibTeX TR2008-089 PDF
      • @inproceedings{Mohan2008jun,
      • author = {Mohan, A. and Huang, X. and Tumblin, J. and Raskar, R.},
      • title = {Sensing Increased Image Resolution Using Aperture Masks},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2008,
      • pages = {1--8},
      • month = jun,
      • issn = {1063-6919},
      • url = {https://www.merl.com/publications/TR2008-089}
      • }
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  • Research Area:

    Computer Vision

We present a technique to construct increased-resolution images from multiple photos taken without moving the camera or the sensor. Like other super-resolution techniques, we capture and merge multiple images, but instead of moving the camera sensor by sub-pixel distance for each image, we change masks in the lens aperture and slightly defocus the lens. The resulting capture system is simpler, and tolerates modest mask registration errors well. We present a theoretical analysis of the camera and image merging method, show both simulated results and actual results from a crudely modified consumer camera, and compare its results to robust 'blind' methods that rely on uncontrolled camera displacements.

 

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      Brief
      • The papers "Non-Refractive Modulators for Encoding and Capturing Scene Appearance and Depth" by Veeraraghavan, A., Agrawal, A., Raskar, R., Mohan, A. and Tumblin, J., "Feature Transformation of Biometric Templates for Secure Biometric Systems based on Error Correcting Codes" by Sutcu, Y., Rane, S., Yedidia, J.S., Draper, S.C. and Vetro, A., "Constant Time O(1) Bilateral Filtering" by Porikli, F., "Learning on Lie Groups for Invariant Detection and Tracking" by Tuzel, O., Porikli, F. and Meer, P., "Kernel Integral Images: A Framework for Fast non-Uniform Filtering" by Hussein, M., Porikli, F. and Davis, L., "A Conditional Random Field for Automatic Photo Editing" by Brand, M. and Pletscher, P., "Boosting Adaptive Linear Weak Classifiers for Online Learning and Tracking" by Parag, T., Porikli, F. and Elgammai, A. and "Sensing Increased Image Resolution Using Aperture Masks" by Mohan, A., Huang, X., Tumblin, J. and Raskar, R. were presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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