Objective quality prediction of image retargeting algorithms

Liang, Yun ; Liu, Yong Lin ; Gutierrez, Diego (Universidad de Zaragoza)

Resumen: Quality assessment of image retargeting results is useful when comparing different methods. However, performing the necessary user studies is a long, cumbersome process. In this paper, we propose a simple yet efficient objective quality assessment method based on five key factors: i) preservation of salient regions; ii) analysis of the influence of artifacts; iii) preservation of the global structure of the image; iv) compliance with well-established aesthetics rules; and v) preservation of symmetry. Experiments on the RetargetMe benchmark, as well as a comprehensive additional user study, demonstrate that our proposed objective quality assessment method outperforms other existing metrics, while correlating better with human judgements. This makes our metric a good predictor of subjective preference.

Idioma: Inglés

DOI: 10.1109/TVCG.2016.2517641

Año: 2017

Publicado en: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 23, 2 (2017), 1099-1110
ISSN: 1077-2626

Factor impacto JCR: 3.078 (2017)

Categ. JCR: COMPUTER SCIENCE, SOFTWARE ENGINEERING rank: 8 / 104 = 0.077 (2017) - Q1 - T1

Factor impacto SCIMAGO: 0.869 - Computer Graphics and Computer-Aided Design (Q1) - Software (Q1) - Signal Processing (Q1) - Computer Vision and Pattern Recognition (Q1)

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)