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Depth enhancement through correlation‐based guided filtering in shape from focus
Author(s) -
Ali Usman,
Mahmood Muhammad Tariq
Publication year - 2021
Publication title -
microscopy research and technique
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 118
eISSN - 1097-0029
pISSN - 1059-910X
DOI - 10.1002/jemt.23716
Subject(s) - focus (optics) , volume (thermodynamics) , depth map , artificial intelligence , computer vision , measure (data warehouse) , computer science , image (mathematics) , depth of field , image quality , sequence (biology) , mathematics , optics , data mining , physics , genetics , quantum mechanics , biology
Mostly, shape‐from‐focus (SFF) techniques do not consider any guidance or prior information from the input image sequence while improving the depth information. Consequently, the resultant depth maps may have inaccuracies due to missing the fine structural details. In this paper, we propose a depth enhancement method based on a novel guidance map and guided filtering. In the proposed method, first, a focus measure is applied on image sequence (volume) to compute the focus volume and an initial depth map is obtained by maximizing the focus measure in the optical direction. The guidance map is computed based on the correlation among the image volume and the focus volume along the optical axis. Finally, the improved depth map is obtained by applying guided filtering of initial depth by incorporating the weights from the suggested guidance map. Experiments were carried out using synthetic and real and microscopic image sequences of various objects. Experimental results have demonstrated the effectiveness of the proposed method and a reasonable improvement has been achieved in the quality of reconstructed depth maps.