Energy minimization for image focus volume in shape from focus

In shape from focus (SFF) methods, the quality of depth map is mainly dependent on the accuracy level of image focus volume. Most of the SFF techniques optimize focus volume without incorporating any prior or additional structural information about the scene and thus resultant depth maps are deteriorated. We mitigate this deficiency by proposing to optimize focus volume through energy minimization. The proposed energy function contains smoothness and structural similarity along with data term. Smoothness constraint enforces spatial coherence while structural similarity constraint tries to preserve structures which are consistent with image sequence. This results in an optimized focus volume that imitates the underlying scene accurately. For the implementation of our 3D objective function, we employ an efficient technique that decomposes the problem into a sequence of 1D simple sub-problems. Experiments conducted on synthetic and real image sequences from a variety of datasets demonstrate that the proposed method optimizes the focus volume effectively and thus provides improved depth maps. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

In shape from focus (SFF) methods, the quality of depth maps depends on the accurate optimization of the focus volume. This study proposes optimizing the focus volume through energy minimization, incorporating smoothness and structural similarity constraints to improve image quality.