Autor/Autorin: Jang Jinbeum
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.
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.
Über den Autor
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.
Klappentext
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.
