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Papers/Adaptive Weighted Guided Image Filtering for Depth Enhance...

Adaptive Weighted Guided Image Filtering for Depth Enhancement in Shape-From-Focus

Yuwen Li, Zhengguo Li, Chaobing Zheng, Shiqian Wu

2022-01-18Spectral Reconstruction
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Abstract

Existing shape from focus (SFF) techniques cannot preserve depth edges and fine structural details from a sequence of multi-focus images. Moreover, noise in the sequence of multi-focus images affects the accuracy of the depth map. In this paper, a novel depth enhancement algorithm for the SFF based on an adaptive weighted guided image filtering (AWGIF) is proposed to address the above issues. The AWGIF is applied to decompose an initial depth map which is estimated by the traditional SFF into a base layer and a detail layer. In order to preserve the edges accurately in the refined depth map, the guidance image is constructed from the multi-focus image sequence, and the coefficient of the AWGIF is utilized to suppress the noise while enhancing the fine depth details. Experiments on real and synthetic objects demonstrate the superiority of the proposed algorithm in terms of anti-noise, and the ability to preserve depth edges and fine structural details compared to existing methods.

Results

TaskDatasetMetricValueModel
Image RestorationARAD-1KMRAE0.25AWAN
Image RestorationARAD-1KPSNR31.22AWAN
Image RestorationARAD-1KRMSE0.0367AWAN
10-shot image generationARAD-1KMRAE0.25AWAN
10-shot image generationARAD-1KPSNR31.22AWAN
10-shot image generationARAD-1KRMSE0.0367AWAN

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