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초록· 키워드
오류제보하기
Depth calculation of objects in a scene from images is one of the most studied processes in the fields of image processing, computer vision, and photogrammetry. Conventionally, depth is calculated using a pair of overlapped images captured at different view points. However, there have been studies to calculate depths from a single image. Theoretically, it is known to be possible to calculate depth using the diameter of CoC (Circle of Confusion) caused by defocus under the assumption of a thin lens model. Thus, this study aims to verify the validity of the thin lens model to calculate depth from edge blur amount which corresponds to the radius of CoC. For this study, a commercially available DSLR (Digital Single Lens Reflex) camera was used to capture a set of target sheets which had different edge contrasts. In order to find out the pattern of the variations of edge blur against varying combination of FD (Focusing Distance) and OD (Object Distance), the camera was set to varying FD and target sheet images were captured at varying OD under each FD. Then, the edge blur and edge displacement were estimated from edge slope profiles using a brute-force method. The experimental results show that the pattern of the variations of edge blur observed in the target images was apart from their corresponding theoretical amounts derived under the thin lens assumption but can still be utilized to calculate depth from a single image for the cases similar to the limited conditions experimented under which the tendency between FD and OD is manifest.
목차
Abstract
1. Introduction
2. Methodology
3. Experiments
4. Conclusion
References
참고문헌 (26)
참고문헌 신청
Cao, Y., Fang, S., and Wang, Z. (2013), Digital multifocusing from a single photograph taken with an uncalibrated conventional camera, IEEE Transactions on Image Processing, Vol. 22, No. 9, pp. 3703-3714.
Chen, S.-J. and Shen, H.-L. (2015), Multispectral image outof- focus deblurring using interchannel correlation, IEEE Transactions on Image Processing, Vol. 24, No. 11, pp. 4433-4445.
De, I., Chanda, B., and Chattopadhyay, B. (2006), Enhancing effective depth-of-field by image fusion using mathematical morphology, Image and Vision Computing, Vol. 24, pp. 1278-1287.
Gajjar, R. and Zaveri, T. (2017), Defocus blur parameter estimation using polynomial expression and signature based methods, 4th International Conference on Signal Processing and Integrated Networks, 2-3 February, Noida, India, pp. 71-75.
Green, P., Sun, W., Matusik, W., and Durand, F. (2007), Multi-aperture photography, ACM Transactions on Graphics, Vol. 26, No. 3, Article 68.
Chen, S.-J. and Shen, H.-L. (2015), Multispectral image outof- focus deblurring using interchannel correlation, IEEE Transactions on Image Processing, Vol. 24, No. 11, pp. 4433-4445.
De, I., Chanda, B., and Chattopadhyay, B. (2006), Enhancing effective depth-of-field by image fusion using mathematical morphology, Image and Vision Computing, Vol. 24, pp. 1278-1287.
Gajjar, R. and Zaveri, T. (2017), Defocus blur parameter estimation using polynomial expression and signature based methods, 4th International Conference on Signal Processing and Integrated Networks, 2-3 February, Noida, India, pp. 71-75.
Green, P., Sun, W., Matusik, W., and Durand, F. (2007), Multi-aperture photography, ACM Transactions on Graphics, Vol. 26, No. 3, Article 68.
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