Sensor-Based Auto-Focusing System Using Multi-Scale Feature Extraction and Phase Correlation Matching

This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution featu...

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Bibliographic Details
Main Authors: Jinbeum Jang, Yoonjong Yoo, Jongheon Kim, Joonki Paik
Format: Article
Language:English
Published: MDPI AG 2015-03-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/15/3/5747
Description
Summary:This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing 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. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector 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 faster, more robust auto focusing than existing systems.
ISSN:1424-8220