@inproceedings{30640ba09f6645b1a0906d434b59305d,
title = "3-D shape recovery from image focus using rank transform",
abstract = "Obtaining an accurate and precise depth map is an ultimate goal of 3-D shape recovery. This article proposes a new robust algorithm Rank Transform (RT) for recovering 3-D shape of an object. The rank transform (RT) encodes for each pixel the position of its grey value in the ranking of all the grey values in its neighborhood. Due to its low computational complexity and robustness against noise, it is superior alternative to most of other SFF approaches. The proposed method is experimented using real and synthetic image sequences. The evaluation is gauged on the basis of unimodality and monotonicity of the focus curve. Finally by means of two global statistical metrics Root mean square error (RMSE) and correlation, we show that our method produces – in spite of simplicity- results of competitive quality.",
author = "Fahad Mahmood and Jawad Mahmood and Qureshi, {Waqar Shahid} and Khan, {Umar Shahbaz}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 12th International Symposium on Visual Computing, ISVC 2016 ; Conference date: 12-12-2016 Through 14-12-2016",
year = "2016",
doi = "10.1007/978-3-319-50832-0_50",
language = "English",
isbn = "9783319508313",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "514--523",
editor = "George Bebis and Darko Koracin and Tobias Isenberg and Sandra Skaff and Amela Sadagic and Richard Boyle and Fatih Porikli and Jianyuan Min and Carlos Scheidegger and Alireza Entezari and Bahram Parvin and Daisuke Iwai",
booktitle = "Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings",
}