J
Jiheng Wang
Researcher at University of Waterloo
Publications - 30
Citations - 533
Jiheng Wang is an academic researcher from University of Waterloo. The author has contributed to research in topics: Image quality & Stereoscopy. The author has an hindex of 11, co-authored 30 publications receiving 446 citations. Previous affiliations of Jiheng Wang include Food and Drug Administration.
Papers
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Journal ArticleDOI
Quality Prediction of Asymmetrically Distorted Stereoscopic 3D Images
TL;DR: A binocular rivalry-inspired multi-scale model to predict the quality of stereoscopic images from that of the single-view images is proposed, and the results show that the proposed model successfully eliminates the prediction bias, leading to significantly improved quality prediction of the stereoscope images.
Journal ArticleDOI
Asymmetrically Compressed Stereoscopic 3D Videos: Quality Assessment and Rate-Distortion Performance Evaluation
Jiheng Wang,Shiqi Wang,Zhou Wang +2 more
TL;DR: A binocular rivalry inspired model is applied to account for the prediction bias, leading to a significantly improved full reference quality prediction model of stereoscopic videos that allows us to quantitatively predict the coding gain of different variations of asymmetric video compression, and provides new insight on the development of high efficiency 3D video coding schemes.
Journal ArticleDOI
Image classification based on complex wavelet structural similarity
TL;DR: Experiments show that a conceptually simple image classification method, which does not involve any registration, intensity normalization or sophisticated feature extraction processes, and does not rely on any modeling of the image patterns or distortion processes, achieves competitive performance with reduced computational cost.
Proceedings ArticleDOI
Quality prediction of asymmetrically distorted stereoscopic images from single views
Jiheng Wang,Kai Zeng,Zhou Wang +2 more
TL;DR: An information-content and divisive normalization based pooling scheme that improves upon SSIM in estimating the quality of single view images and a binocular rivalry inspired model to predict thequality of stereoscopic images based on that of thesingle view images are proposed.
Proceedings ArticleDOI
Perceptual quality assessment of high frame rate video
TL;DR: It is observed that perceived video quality generally increases with frame rate, but the gain saturates at high rates, and such gain also depends on the interactions between quantization level, spatial resolution, and spatial and motion complexities.