Shape from focus (SFF) reconstructs 3D shape of the scene from a sequence of multi-focus
images, and the quality of reconstructed shape mainly depends on the accuracy of image …

Abstract Depth-from-focus (DFF) is a technique that infers depth using the focus change of a
camera. In this work, we propose a convolutional neural network (CNN) to find the best …

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 …

A light field camera can record image information of the same scene from different
viewpoints. Its 4D data allow post processing among which digital refocusing is popular due …

Shape from focus (SFF) is a technique for reconstructing the 3D shape of a scene from a
sequence of multi-focus images. The quality of the shape reconstruction depends on the …

The 3D reconstruction of freedom surface has been a major challenge for computer vision
as well as metrology. Complex surface structures such as large undulations and deep …

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 affects the …

Estimating a 3D shape from 2D images is a classic computer vision problem. Shape from
focus is a commonly used method for this purpose. With shape from focus, 3D depth is …

For better photography, most recent commercial cameras including smartphones have either
adopted large-aperture lens to collect more light or used a burst mode to take multiple …

Three‐dimensional shape recovery is an important issue in the field of computer vision.
Shape from Focus (SFF) is one of the passive techniques that uses focus information to …