Analyzing the Geometric Distortions in a Chinese Scholar Garden in the Lin Family Mansion and Garden Using Computer-Simulated Projections

2021 ◽  
Vol 18 (5) ◽  
pp. 1119-1130
Author(s):  
Nan-Ching Tai
Keyword(s):  
Chinese Scholar ◽  
Geometric Distortions

Real-Time Compressed- Domain Video Watermarking Resistance to Geometric Distortions

2012 ◽  
Vol 19 (1) ◽  
pp. 70-79 ◽  
Author(s):  
Liyun Wang ◽  
Hefei Ling ◽  
Fuhao zou ◽  
Zhengding Lu
Keyword(s):  
Real Time ◽  
Video Watermarking ◽  
Compressed Domain ◽  
Geometric Distortions

Wu Ch'i-chun: Profile of a Chinese Scholar-Technologist

1965 ◽  
Vol 6 (3) ◽  
pp. 394
Author(s):  
E-tu Zen Sun
Keyword(s):  
Chinese Scholar

A Tris(trifluoromethyl)antimony Adduct of a Nucleophilic Carbene: Geometric Distortions in Carbene Adducts

1999 ◽  
Vol 625 (11) ◽  
pp. 1813-1817 ◽  
Author(s):  
Anthony J. Arduengo, III ◽  
Roland Krafczyk ◽  
Reinhard Schmutzler ◽  
Walter Mahler ◽  
William J. Marshall
Keyword(s):  
Geometric Distortions

Colourlab Image Database: Geometric Distortions

2021 ◽  
Vol 2021 (29) ◽  
pp. 258-263
Author(s):  
Marius Pedersen ◽  
Seyed Ali Amirshahi
Keyword(s):  
Image Quality ◽  
High Performance ◽  
Image Database ◽  
Quality Metrics ◽  
Current Image ◽  
Geometric Distortions ◽  
Image Quality Metrics ◽  
Objective Metrics ◽  
Reference Images

Over the years, a high number of different objective image quality metrics have been proposed. While some image quality metrics show a high correlation with subjective scores provided in different datasets, there still exists room for improvement. Different studies have pointed to evaluating the quality of images affected by geometrical distortions as a challenge for current image quality metrics. In this work, we introduce the Colourlab Image Database: Geometric Distortions (CID:GD) with 49 different reference images made specifically to evaluate image quality metrics. CID:GD is one of the first datasets which include three different types of geometrical distortions; seam carving, lens distortion, and image rotation. 35 state-ofthe-art image quality metrics are tested on this dataset, showing that apart from a handful of these objective metrics, most are not able to show a high performance. The dataset is available at <ext-link ext-link-type="url" xlink:href="http://www.colourlab.no/cid">www.colourlab.no/cid</ext-link>.

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