Perceptual Quality Assessment of Omnidirectional Images: Subjective Experiment and Objective Model Evaluation

Perceptual Quality Assessment of Omnidirectional Images: Subjective Experiment and Objective Model Evaluation

DUAN Huiyu, ZHAI Guangtao, MIN Xiongkuo, ZHU Yucheng, FANG Yi, and YANG Xiaokang

(Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract: Virtual reality (VR) environment can provide immersive experience to viewers. Under the VR environment, providing a good quality of experience is extremely important. Therefore, in this paper, we present an image quality assessment (IQA) study on omnidirectional images. We first build an omnidirectional IQA (OIQA) database, including 16 source images with their corresponding 320 distorted images. We add four commonly encountered distortions. These distortions are JPEG compression, JPEG2000 compression, Gaussian blur, and Gaussian noise. Then we conduct a subjective quality evaluation study in the VR environment based on the OIQA database. Considering that visual attention is more important in VR environment, head and eye movement data are also tracked and collected during the quality rating experiments. The 16 raw and their corresponding distorted images, subjective quality assessment scores, and the head-orientation data and eye-gaze data together constitute the OIQA database. Based on the OIQA database, we tested some state-of-the-art full-reference IQA (FR-IQA) measures on equirectangular format or cubic format omnidirectional images. The results show that applying FR-IQA metrics on cubic format omnidirectional images could improve their performance. The performance of some FR-IQA metrics combining the saliency weight of 3 different types are also tested based on our database. Some new phenomena different from traditional IQA are observed.
Keywords: perceptual quality assessment; omnidirectional images; subjective experiment; objective model evaluation; visual saliency