Deep Autoencoder Multi-Exposure HDR Imaging

A. Omrani, M. Soheili, M. Kelarestaghi
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Abstract

Recently, in the era of photography, due to capturing images with limited dynamic range by cameras, High Dynamic Range (HDR) imaging has engrossed people’s attention because HDR pictures present more details and better luminance than images with Low Dynamic Range (LDR). Moreover, produced HDR images by a single LDR image cannot reconstruct details appropriately, and therefore, in this research, a deep learning method is proposed to generate an HDR picture by multiple LDR pictures with different exposures. The experiments and results illustrate that the proposed algorithm performs better than the other methods in quantitative and visual comparison.
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深度自动编码器多曝光HDR成像
近年来,在摄影时代,由于相机拍摄的图像动态范围有限,高动态范围(High dynamic range, HDR)成像受到了人们的关注,因为HDR图像比低动态范围(Low dynamic range, LDR)图像呈现出更多的细节和更好的亮度。此外,单张LDR图像生成的HDR图像不能很好地重建细节,因此,本研究提出了一种深度学习方法,通过多张不同曝光的LDR图像生成HDR图像。实验和结果表明,该算法在定量和视觉比较方面都优于其他方法。
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