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Image quality assessment: from error visibility to structural similarity
TLDR
A structural similarity index is developed and its promise is demonstrated through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. Expand
A universal image quality index
  • Zhou Wang, A. Bovik
  • Computer Science, Mathematics
  • IEEE Signal Processing Letters
  • 7 August 2002
TLDR
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. Expand
Multiscale structural similarity for image quality assessment
TLDR
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. Expand
No-Reference Image Quality Assessment in the Spatial Domain
TLDR
Despite its simplicity, it is able to show that BRISQUE is statistically better than the full-reference peak signal-to-noise ratio and the structural similarity index, and is highly competitive with respect to all present-day distortion-generic NR IQA algorithms. Expand
Making a “Completely Blind” Image Quality Analyzer
TLDR
This work has recently derived a blind IQA model that only makes use of measurable deviations from statistical regularities observed in natural images, without training on human-rated distorted images, and, indeed, without any exposure to distorted images. Expand
Image information and visual quality
TLDR
An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA. Expand
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
TLDR
This paper presents results of an extensive subjective quality assessment study in which a total of 779 distorted images were evaluated by about two dozen human subjects and is the largest subjective image quality study in the literature in terms of number of images, distortion types, and number of human judgments per image. Expand
Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures
TLDR
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. Expand
Image Quality Assessment: From Error Measurement to Structural Similarity
TLDR
A Structural Similarity Index is developed and its promise is demonstrated through a set of intuitive ex- amples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. Expand
Multi-scale structural similarity for image quality assessment
TLDR
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. Expand
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