Temporally consistent tone mapping of images and video using optimal \(K\)-means clustering

DOI10.1007/s10851-016-0677-1zbMath1409.68315OpenAlexW2483969631WikidataQ59611949 ScholiaQ59611949MaRDI QIDQ2014481

Magnus Oskarsson

Publication date: 25 August 2017

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-016-0677-1

zbMATH Keywords

dynamic programmingclusteringhigh dynamic range imageshigh dynamic range video

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• Silhouettes
• GitHub

Cites Work

• Unnamed Item
• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• NP-hardness of Euclidean sum-of-squares clustering
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• A note on cluster analysis and dynamic programming
• The Planar k-Means Problem is NP-Hard
• Least squares quantization in PCM
• Random Projection Trees for Vector Quantization