Depth enhancement through correlation‐based guided filtering in shape from focus

Ali, Usman; Mahmood, Muhammad Tariq

doi:10.1002/jemt.23716

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…A gradient-based operator was used as the FM operator, and the window size was 21. The compared methods are adaptive window size [27] and guided filtering [28]. The proposed method was used together with a postprocessing algorithm.…”

Section: Implementation In Microscopic Systemmentioning

confidence: 99%

See 1 more Smart Citation

Edge Bleeding Artifact Reduction for Shape from Focus in Microscopic 3D Sensing

Park,

Baek

2023

Sensors

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Shape from focus enables microscopic 3D sensing by combining it with a microscope system. However, edge bleeding artifacts of estimated depth easily occur in this environment. Therefore, this study analyzed artifacts and proposed a method to reduce edge bleeding artifacts. As a result of the analysis, the artifact factors are the depth of field of the lens, object texture, brightness difference between layers, and the slope of the object. Additionally, to reduce artifacts, a weighted focus measure value method was proposed based on the asymmetry of local brightness in artifacts. The proposed reduction method was evaluated through simulation and implementation. Edge bleeding artifact reduction rates of up to 60% were shown in various focus measure operators. The proposed method can be used with postprocessing algorithms and reduces edge bleeding artifacts.

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Section: Implementation In Microscopic Systemmentioning

confidence: 99%

“…However, the edge bleeding artifact cannot be removed because it is not related to the window size. As another method, a correlation-based guide filtering method was proposed [28]. The boundary of the object is made clear by estimating a depth map with a high correlation between the image and FM value.…”

Section: Introductionmentioning

confidence: 99%

Edge Bleeding Artifact Reduction for Shape from Focus in Microscopic 3D Sensing

Park,

Baek

2023

Sensors

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“…Recently, guided filtering algorithms have been applied for SFF to improve depth maps [19,20]. Guided filtering is a technique to obtain the target image with richer details via the structural information of the guided image.…”

Section: Introductionmentioning

confidence: 99%

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

Li¹,

Li²,

Zheng³

et al. 2022

Preprint

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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.

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