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Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference autofocusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide fast, robust auto focusing.

Produktbeschreibung
Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference autofocusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide fast, robust auto focusing.
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Autorenporträt
Jinbeum Jang was born in Suwon, Korea, in 1989. He received the B.S. degree in Digital Media from Sangmyung University, Seoul Korea, in 2014. Currently, he is pursuing a M.S. degree in Image Science at Chung-Ang University, Seoul Korea. His research interests include stereo vision, and auto-focusing.