The field of computational photography, and in particular the design and implementation of coded apertures, has yielded impressive results in the last years. Among their applications lies defocus deblurring, in which we focus in this paper. Following the approach of previous works, we obtain near-optimal coded apertures using a genetic algorithm and an existing quality metric. We perform both synthetic and real experiments, testing the performance of the apertures along the dimensions of depth, size and shape. We additionally explore non-binary apertures, usually overlooked in the literature, and perform a comparative analysis with their binary counterparts.

Categories and Subject Descriptors (according to ACM CCS): I.4.3 [Image Processing and Computer Vision]: Enhancement-Sharpening and deblurring

Belen Masia, Adrian Corrales, Lara Presa, and Diego Gutierrez

V Ibero-American Symposium in Computer Graphics

Displays and Computational Photography

105

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