All-in-focus image reconstruction with depth sensing

2016 ◽  
Author(s):  
Zhong-shan Sui ◽  
Jun-shan Li ◽  
Jing-bo Fan ◽  
Xin-bo Ren ◽  
Yan Li ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Depth Sensing ◽  
Focus Image

All-in-focus image reconstruction robust to ghosting effect

2018 ◽  
Author(s):  
Sergio Gómez Angulo ◽  
Julia R. Alonso ◽  
Marija Strojnik ◽  
Ariel Fernández ◽  
Guillermo García Torales ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Focus Image

All-in-focus image reconstruction under severe defocus

2015 ◽  
Vol 40 (8) ◽  
pp. 1671 ◽  
Author(s):  
Julia R. Alonso ◽  
Ariel Fernández ◽  
Gastón A. Ayubi ◽  
José A. Ferrari
Keyword(s):  
Image Reconstruction ◽  
Focus Image

scholarly journals Construction of All-in-Focus Images Assisted by Depth Sensing

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1409 ◽  
Author(s):  
Hang Liu ◽  
Hengyu Li ◽  
Jun Luo ◽  
Shaorong Xie ◽  
Yu Sun
Keyword(s):  
Image Fusion ◽  
Imaging System ◽  
State Of The Art ◽  
Depth Map ◽  
Depth Of Field ◽  
Depth Sensor ◽  
Depth Sensing ◽  
Focus Image ◽  
Limited Depth ◽  
Image Fusion Method

Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a colour camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.

Multi-Exposure and Multi-Focus Image Fusion in Gradient Domain

2016 ◽  
Vol 25 (10) ◽  
pp. 1650123 ◽  
Author(s):  
Sujoy Paul ◽  
Ioana S. Sevcenco ◽  
Panajotis Agathoklis
Keyword(s):  
Image Reconstruction ◽  
Image Fusion ◽  
Reconstruction Algorithm ◽  
Haar Wavelet ◽  
Reconstruction Technique ◽  
Fusion Algorithm ◽  
Poisson Solver ◽  
Pixel Location ◽  
Focus Image ◽  
Image Reconstruction Technique

A multi-exposure and multi-focus image fusion algorithm is proposed. The algorithm is developed for color images and is based on blending the gradients of the luminance components of the input images using the maximum gradient magnitude at each pixel location and then obtaining the fused luminance using a Haar wavelet-based image reconstruction technique. This image reconstruction algorithm is of [Formula: see text] complexity and includes a Poisson solver at each resolution to eliminate artifacts that may appear due to the nonconservative nature of the resulting gradient. The fused chrominance, on the other hand, is obtained as a weighted mean of the chrominance channels. The particular case of grayscale images is treated as luminance fusion. Experimental results and comparison with other fusion techniques indicate that the proposed algorithm is fast and produces similar or better results than existing techniques for both multi-exposure as well as multi-focus images.

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