In practice, the calibrated orientation parameters can be used for wavefront correction of the SH sensor. The calibrated value of the distance d is a key parameter for super-resolution method of light field image based on wave analysis. Furthermore, the method can be employed for calibrating parameters of a plenoptic camera to retrieve depth information. Because the different distances between an imaging lens and the plenoptic component can also be estimated by using the presented geometric model and similar optimization algorithm with the calibrated value of d.
However, the calibration method
proposed in this PP 2
research is using an optimization algorithm to predict several parameters based on one kind of measurements, the subimage centers. The estimated results are affected by different factors including, the model, optimization algorithm, accuracy of measurements. First, the geometric model simplifies the system, for example, the microlenses are considered as thin lenses and the lens aberrations are neglected. These simplifications might cause variations of the subimage centers and inaccuracy of estimated results. Second, the optimization model assumes that the microlenses are ideally arranged with designed pitch, which is generally not true. This factor can be corrected by designing experiments to calibrating the actual pitches among the microlenses. Third, Excision-repair
optimization algorithm plays a crucial part for predicting the parameters. A better result might be achieved if the algorithm was improved. In conclusion, there are several factors will affect the accuracy of estimated results, such as, variation of white source, variation of the microlens-pitches, microlens aberrations, the efficiency of optimization algorithm. Therefore, future work should be done to thoroughly analyze the uncertainty of this method.
AcknowledgmentThis work is supported by the National Natural Science Foundation of China (Grant no. 61307020).
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