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| Content Provider | ACM Digital Library |
|---|---|
| Author | Agrawal, Amit Wilson, Cyrus A. Veeraraghavan, Ashok Raskar, Ramesh |
| Abstract | Glare arises due to multiple scattering of light inside the camera's body and lens optics and reduces image contrast. While previous approaches have analyzed glare in 2D image space, we show that glare is inherently a 4D ray-space phenomenon. By statistically analyzing the ray-space inside a camera, we can classify and remove glare artifacts. In ray-space, glare behaves as high frequency noise and can be reduced by outlier rejection. While such analysis can be performed by capturing the light field inside the camera, it results in the loss of spatial resolution. Unlike light field cameras, we do not need to reversibly encode the spatial structure of the ray-space, leading to simpler designs. We explore masks for uniform and non-uniform ray sampling and show a practical solution to analyze the 4D statistics without significantly compromising image resolution. Although diffuse scattering of the lens introduces 4D low-frequency glare, we can produce useful solutions in a variety of common scenarios. Our approach handles photography looking into the sun and photos taken without a hood, removes the effect of lens smudges and reduces loss of contrast due to camera body reflections. We show various applications in contrast enhancement and glare manipulation. |
| Starting Page | 1 |
| Ending Page | 10 |
| Page Count | 10 |
| File Format | PDF QT / MOV |
| ISBN | 9781450301121 |
| DOI | 10.1145/1399504.1360655 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2008-08-11 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Flare Glare Light fields Computational photography Masks |
| Content Type | Video Text |
| Resource Type | Article |
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