Data merging for the cultural heritage imaging based on Chebfun approach

Mariem El Afrit, Yann Le Du, Rafaël Del Pino, Guolin Zhang


Cultural heritage imaging has specific needs with regards to the analysis of images that require the manipulation of a single digital object that combines the images obtained from different instruments probing different scales at different wavelengths, with the further possibility of selecting two or three dimensional representations. We propose a unified imaging data processing approach based on the "Chebyshev Technology" using the open source software Chebfun which, by mapping data processing to simple polynomial transformations, brought considerable improvements over already existing procedures. Within that same data processing framework we may further investigate how to merge images originating from different acquisition devices since all images are expressed in the same basis (an approximate Chebfun polynomial basis ) before being merged. In the end, we hope to map all imaging data processing to simple polynomial operations. Our massive data-sets required parallelizing some Chebfun functions on GPUs, allowing about 100 times faster polynomial evaluation and up to 12 times faster on CPUs when parallelizing the whole algorithm.

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