Identification and correction of microlens array rotation error in plenoptic imaging systems. (October 2019)

• Record Type: Journal Article
• Authors: Li, Suning; Yuan, Yuan; Shen, Siyuan; Tan, Heping
• Is Part Of: Optics and lasers in engineering. Volume 121(2019)
• Page Start: 156
• Page End: 168
• Publication Date: 2019-10
• Subjects: Calibration -- Rotation error -- Light field -- Microlens array -- Plenoptic imaging systems; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2019.04.008
• Languages: English
• ISSNs: 0143-8166

Abstract

High lights: An MLA rotation error model is formulated to derive the transformations between the error point and its ideal point of ray projection. The error imaging characteristics and degradation mechanism is analyzed. A novel correction method for MLA rotation error is proposed. Abstract: Plenoptic imaging systems can acquire spatio-angular information of light rays, allowing complex scene measurements with a single exposure. The measurement accuracy is significantly affected by the orientation parameters of internal components in the system, especially the rotation error between the microlens array (MLA) and the image sensor. In this paper, we formulate an MLA rotation error model to derive the transformations between the error point and its ideal point of ray projection. Furthermore, we present a method for identifying and correcting the rotation error, including error angle estimation, raw image rotation, and refocused image reverse rotation. Through simulation experiments, the imaging characteristics of the MLA rotation error are analyzed and the performance of the proposed model and method are verified. The results demonstrate that the integral distribution of raw image distortion caused by the error is centrosymmetric. In the error range of 0.1–1.0°, the mean square error (MSE) and structural similarity index metric (SSIM) of the corrected refocused images are improved to 0.2146–3.8190 and 0.9986–0.9999, respectively.