| 1. |
- Johansson, Eija, 1982, et al.
(författare)
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Interpolation based on stationary and adaptive AR(1) modeling
- 2011
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Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 4052-4055
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Konferensbidrag (refereegranskat)abstract
- In this paper, we describe a minimal mean square error (MMSE) optimal interpolation filter for discrete random signals. We explicitly derive the interpolation filter for a first-order autoregressive process (AR(1)), and show that the filter depends only on the two adjacent points. The result is extended by developing an algorithm called local AR approximation (LARA), where a random signal is locally estimated as an AR(1) process. Experimental evaluation illustrates that LARA interpolation yields a lower mean square error than other common interpolation techniques, including linear, spline and local polynomial approximation (LPA).
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| 2. |
- Ström, Marie, 1984, et al.
(författare)
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Mapping colors from paintings to tapestries: Rejuvenating the faded colors in tapestries based on colors in reference paintings
- 2012
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 0277-786X .- 1996-756X. - 9780819489425 ; 8291, s. Art. no. 82911F-
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Konferensbidrag (refereegranskat)abstract
- We addressed the problem of recovering or "rejuvenating" colors in a faded tapestry (the target image) by automatically mapping colors from digital images of the reference painting or cartoon (the source image). We divided the overall computational challenge into several subproblems, and implemented their solutions in Matlab: 1) quantizing the colors in both the tapestry and the referent painting, 2) matching corresponding regions in the works based on spatial location, area and color, 3) mapping colors from regions in the source image to corresponding regions in the target image, and 4) estimating the fading of colors and excluding color mapping of areas where color has not faded. There are a number of semi-global design parameters in our algorithm, which we currently set by hand, for instance the parameter that balance the effects of 1) matching color areas in the two images and 2) matching the spatial locations between the two images. We demonstrated our method on synthetic data and on small portions of 16th-century European tapestries of cultural patrimony. Our first steps in a proof-of-concept work suggest that future refinements to our method will lead to a software tool of value to art scholars.
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