• Publications
  • Influence
No-Reference Image Quality Assessment in the Spatial Domain
We propose a natural scene statistic-based distortion-generic blind/no-reference (NR) image quality assessment (IQA) model that operates in the spatial domain. The new model, dubbedExpand
  • 1,866
  • 419
  • PDF
Multiscale structural similarity for image quality assessment
The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore aExpand
  • 2,060
  • 393
Making a “Completely Blind” Image Quality Analyzer
An important aim of research on the blind image quality assessment (IQA) problem is to devise perceptual models that can predict the quality of distorted images with as little prior knowledge of theExpand
  • 1,463
  • 332
  • PDF
Image information and visual quality
Measurement of visual quality is of fundamental importance to numerous image and video processing applications. The goal of quality assessment (QA) research is to design algorithms that canExpand
  • 1,733
  • 290
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess theExpand
  • 1,919
  • 206
  • PDF
Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures
In this article, we have reviewed the reasons why we (collectively) want to love or leave the venerable (but perhaps hoary) MSE. We have also reviewed emerging alternative signal fidelity measuresExpand
  • 1,925
  • 202
  • PDF
Image Quality Assessment: From Error Measurement to Structural Similarity
Objective methods for assessing perceptual im- age quality traditionally attempt to quantify the visibility of errors (dierences) between a distorted image and a ref- erence image using a variety ofExpand
  • 999
  • 177
  • PDF
Multi-scale structural similarity for image quality assessment
The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore aExpand
  • 1,074
  • 176
  • PDF
Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
Our approach to blind image quality assessment (IQA) is based on the hypothesis that natural scenes possess certain statistical properties which are altered in the presence of distortion, renderingExpand
  • 1,041
  • 171
  • PDF
Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain
We develop an efficient general-purpose blind/no-reference image quality assessment (IQA) algorithm using a natural scene statistics (NSS) model of discrete cosine transform (DCT) coefficients. TheExpand
  • 1,012
  • 147
  • PDF