Local error and its identification for microlens array in plenoptic camera

A microlens array (MLA) is a key optical element in light-field imaging, but surface errors caused by manufacturing defects can result in the loss and deviation of light-field information transmission. To address this issue, we establish a local error model for an MLA arranged in a matrix form, and develop a method for identifying error microlenses based on image quality evaluation indexes. The local imaging characteristics and degradation mechanism of three basic errors are analyzed through simulation. The local errors on different microlenses cause different degradations of the corresponding sub-images, and the trend of change in light-field image quality is related to the error type, error value, and error direction. The simulation results also verify the accuracy and effectiveness of the proposed method and models.