Color Image Database HTID for Verification of No-Reference Metrics : Peculiarities and Preliminary Results

Autor: Sheyda Ghanbaralizadeh Bahnemiri, Mykola Ponomarenko, Jussi Hakala, Vladimir V. Lukin, Oleg Ieremeiev, Veli-Tapani Peltoketo, Karen Egiazarian
Přispěvatelé: Beghdadi, A., Cheikh, F. Alaya, Tavares, J.M.R.S., Mokraoui, A., Valenzise, G., Oudre, L., Qureshi, M.A., Tampere University, Computing Sciences
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: EUVIP
Popis: The paper describes a new image database HTID for verification and training of no-reference image visual quality metrics. The database contains 2880 color images of size 1536×1024 pixels cropped from the real-life photos produced by the mobile phone cameras with various shooting and post-processing settings. Mean opinion scores for images of the database are obtained. Peculiarities of the database are considered. A comparative analysis of the state-of-The-Art no-reference image visual quality metrics is carried out. It is shown that the proposed database takes its own unique place in the existing image databases and can be effectively used for metrics' verification. acceptedVersion
Databáze: OpenAIRE