H. Sheikh

Publications41
h-index20
Citations39,793
Highly Influential Citations7,055
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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.
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.
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.
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.
Image information and visual quality
  • H. Sheikh, A. Bovik
  • Computer Science, Medicine
    IEEE International Conference on Acoustics…
  • 17 May 2004
TLDR
This work proposes an information fidelity criterion that quantifies the Shannon information that is shared between the reference and distorted images relative to the information contained in the reference image itself, and demonstrates the performance of the algorithm by testing it on a data set of 779 images.
An information fidelity criterion for image quality assessment using natural scene statistics
TLDR
This paper proposes a novel information fidelity criterion that is based on natural scene statistics and derives a novel QA algorithm that provides clear advantages over the traditional approaches and outperforms current methods in testing.
No-reference perceptual quality assessment of JPEG compressed images
TLDR
It is shown that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality and tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics.
No-reference quality assessment using natural scene statistics: JPEG2000
TLDR
It is claimed that natural scenes contain nonlinear dependencies that are disturbed by the compression process, and that this disturbance can be quantified and related to human perceptions of quality.
OBJECTIVE VIDEO QUALITY ASSESSMENT
Digital video data, stored in video databases and distributed through communication networks, is subject to various kinds of distortions during acquisition, compression, processing, transmission, and…
Quality-aware images
TLDR
A practical quality-aware image encoding, decoding and quality analysis system, which employs a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.
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