IEEE Trans Image Process - Probabilistic exposure fusion.

Tópicos

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Resumo

The luminance of a natural scene is often of high dynamic range (HDR). In this paper, we propose a new scheme to handle HDR scenes by integrating locally adaptive scene detail capture and suppressing gradient reversals introduced by the local adaptation. The proposed scheme is novel for capturing an HDR scene by using a standard dynamic range (SDR) device and synthesizing an image suitable for SDR displays. In particular, we use an SDR capture device to record scene details (i.e., the visible contrasts and the scene gradients) in a series of SDR images with different exposure levels. Each SDR image responds to a fraction of the HDR and partially records scene details. With the captured SDR image series, we first calculate the image luminance levels, which maximize the visible contrasts, and then the scene gradients embedded in these images. Next, we synthesize an SDR image by using a probabilistic model that preserves the calculated image luminance levels and suppresses reversals in the image luminance gradients. The synthesized SDR image contains much more scene details than any of the captured SDR image. Moreover, the proposed scheme also functions as the tone mapping of an HDR image to the SDR image, and it is superior to both global and local tone mapping operators. This is because global operators fail to preserve visual details when the contrast ratio of a scene is large, whereas local operators often produce halos in the synthesized SDR image. The proposed scheme does not require any human interaction or parameter tuning for different scenes. Subjective evaluations have shown that it is preferred over a number of existing approaches.

Resumo Limpo

lumin natur scene often high dynam rang hdr paper propos new scheme handl hdr scene integr local adapt scene detail captur suppress gradient revers introduc local adapt propos scheme novel captur hdr scene use standard dynam rang sdr devic synthes imag suitabl sdr display particular use sdr captur devic record scene detail ie visibl contrast scene gradient seri sdr imag differ exposur level sdr imag respond fraction hdr partial record scene detail captur sdr imag seri first calcul imag lumin level maxim visibl contrast scene gradient embed imag next synthes sdr imag use probabilist model preserv calcul imag lumin level suppress revers imag lumin gradient synthes sdr imag contain much scene detail captur sdr imag moreov propos scheme also function tone map hdr imag sdr imag superior global local tone map oper global oper fail preserv visual detail contrast ratio scene larg wherea local oper often produc halo synthes sdr imag propos scheme requir human interact paramet tune differ scene subject evalu shown prefer number exist approach

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