Z
Zhou Wang
Researcher at University of Waterloo
Publications - 330
Citations - 36708
Zhou Wang is an academic researcher from University of Waterloo. The author has contributed to research in topics: Image quality & Image processing. The author has an hindex of 63, co-authored 256 publications receiving 30562 citations. Previous affiliations of Zhou Wang include South China University of Technology & City University of Hong Kong.
Papers
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Journal ArticleDOI
A universal image quality index
Zhou Wang,Alan C. Bovik +1 more
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Proceedings ArticleDOI
Multiscale structural similarity for image quality assessment
TL;DR: This paper proposes a multiscale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions, and develops an image synthesis method to calibrate the parameters that define the relative importance of different scales.
Journal ArticleDOI
Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures
Zhou Wang,Alan C. Bovik +1 more
TL;DR: This article has reviewed the reasons why people want to love or leave the venerable (but perhaps hoary) MSE and reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems.
Proceedings Article
Multi-scale structural similarity for image quality assessment
TL;DR: This paper proposes a multi-scale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions, and develops an image synthesis method to calibrate the parameters that define the relative importance of different scales.
Journal ArticleDOI
Information Content Weighting for Perceptual Image Quality Assessment
Zhou Wang,Qiang Li +1 more
TL;DR: This paper aims to test the hypothesis that when viewing natural images, the optimal perceptual weights for pooling should be proportional to local information content, which can be estimated in units of bit using advanced statistical models of natural images.