Detail publikace

Learning to Predict Localized Distortions in Rendered Images

ČADÍK, M. HERZOG, R. MANTIUK, R. MANTIUK, R. MYSZKOWSKI, K. SEIDEL, H.

Originální název

Learning to Predict Localized Distortions in Rendered Images

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

In this work, we present an analysis of feature descriptors for objective image quality assessment. We explore a large space of possible features including components of existing image quality metrics as well as many traditional computer vision and statistical features. Additionally, we propose new features motivated by human perception and we analyze visual saliency maps acquired using an eye tracker in our user experiments. The discriminative power of the features is assessed by means of a machine learning framework revealing the importance of each feature for image quality assessment task. Furthermore, we propose a new data-driven full-reference image quality metric which outperforms current state-of-the-art metrics. The metric was trained on subjective ground truth data combining two publicly available datasets. For the sake of completeness we create a new testing synthetic dataset including experimentally measured subjective distortion maps. Finally, using the same machine-learning framework we optimize the parameters of popular existing metrics.

Klíčová slova

image quality assessment, feature vectors, machine learning, rendering

Autoři

ČADÍK, M.; HERZOG, R.; MANTIUK, R.; MANTIUK, R.; MYSZKOWSKI, K.; SEIDEL, H.

Rok RIV

2013

Vydáno

1. 11. 2013

ISSN

0167-7055

Periodikum

COMPUTER GRAPHICS FORUM

Ročník

2013

Číslo

7

Stát

Spojené království Velké Británie a Severního Irska

Strany od

401

Strany do

410

Strany počet

10

URL

BibTex

@article{BUT103580,
  author="Martin {Čadík} and Robert {Herzog} and Rafał {Mantiuk} and Radosław {Mantiuk} and Karol {Myszkowski} and Hans-Peter {Seidel}",
  title="Learning to Predict Localized Distortions in Rendered Images",
  journal="COMPUTER GRAPHICS FORUM",
  year="2013",
  volume="2013",
  number="7",
  pages="401--410",
  doi="10.1111/cgf.12248",
  issn="0167-7055",
  url="http://cadik.posvete.cz"
}