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2 November 2018 Luminance regionalization-based saliency detection for high dynamic range image
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Abstract
The existing saliency detection methods are not suitable for high dynamic range (HDR) images. In this work, based on human visual system, we propose a new method for detecting the saliency of HDR images via luminance regionalization. First, considering the visual characteristics of a wider luminance range of HDR images, luminance information of the HDR image is extracted, and the HDR image is divided into high, medium, and low luminance regions by luminance thresholding. Then, saliency map of each luminance region is detected, respectively. Color and texture features are extracted for the high luminance region, luminance and texture features are extracted for the low luminance region, and an existing LDR image saliency detection method is used for the medium luminance region. Finally, the three saliency maps are linearly fused to obtain the final HDR image saliency map. Experimental results on two public databases (EPFL HDR eye tracking database and TMID database) demonstrate that the proposed method performs well when against the five state-of-the-art methods in terms of detecting the salient regions of HDR images.
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Junjun Zhang, Mei Yu, Yang Song, Hua Shao, and Gangyi Jiang "Luminance regionalization-based saliency detection for high dynamic range image", Proc. SPIE 10817, Optoelectronic Imaging and Multimedia Technology V, 1081716 (2 November 2018); https://doi.org/10.1117/12.2502042
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