The diffractive achromat full spectrum computational imaging with diffractive optics
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center (VCC)
Computer Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/621419
MetadataShow full item record
AbstractDiffractive optical elements (DOEs) have recently drawn great attention in computational imaging because they can drastically reduce the size and weight of imaging devices compared to their refractive counterparts. However, the inherent strong dispersion is a tremendous obstacle that limits the use of DOEs in full spectrum imaging, causing unacceptable loss of color fidelity in the images. In particular, metamerism introduces a data dependency in the image blur, which has been neglected in computational imaging methods so far. We introduce both a diffractive achromat based on computational optimization, as well as a corresponding algorithm for correction of residual aberrations. Using this approach, we demonstrate high fidelity color diffractive-only imaging over the full visible spectrum. In the optical design, the height profile of a diffractive lens is optimized to balance the focusing contributions of different wavelengths for a specific focal length. The spectral point spread functions (PSFs) become nearly identical to each other, creating approximately spectrally invariant blur kernels. This property guarantees good color preservation in the captured image and facilitates the correction of residual aberrations in our fast two-step deconvolution without additional color priors. We demonstrate our design of diffractive achromat on a 0.5mm ultrathin substrate by photolithography techniques. Experimental results show that our achromatic diffractive lens produces high color fidelity and better image quality in the full visible spectrum. © 2016 ACM.
CitationPeng Y, Fu Q, Heide F, Heidrich W (2016) The diffractive achromat full spectrum computational imaging with diffractive optics. ACM Transactions on Graphics 35: 1–11. Available: http://dx.doi.org/10.1145/2897824.2925941.
Conference/Event nameACM SIGGRAPH 2016