• Corpus ID: 29123652

TID2008 – A database for evaluation of full-reference visual quality assessment metrics

  title={TID2008 – A database for evaluation of full-reference visual quality assessment metrics},
  author={Nikolay N. Ponomarenko and Vladimir V. Lukin and Alexander A. Zelensky},
In this paper, a new image database, TID2008, for evaluation of full-reference visual quality assessment metrics is described. It contains 1700 test images (25 reference images, 17 types of distortions for each reference image, 4 different levels of each type of distortion). Mean Opinion Scores (MOS) for this database have been obtained as a result of more than 800 experiments. During these tests, observers from three countries (Finland, Italy, and Ukraine) have carried out about 256000… 

Image database TID 2013 : Peculiarities , results and perspectives

This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics, andMotivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented.

Image database TID2013: Peculiarities, results and perspectives

Image visual quality metrics verification by TID2013: Exploring of mean square error drawbacks

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Merging of MOS of Large Image Databases for No-reference Image Visual Quality Assessment

A simple and effective method of merging of several large databases into one database with transforming of their MOS into one scale is proposed and Merged MOS is used for practical training of no-reference metric.

Analysis of TID2008 and LIVE databases

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Comprehensive evaluation of no-reference image quality assessment algorithms on authentic distortions

  • D. Varga
  • Computer Science, Medicine
  • 2020
This study evaluates several machine learning based NR-IQA methods and one opinion unaware method on databases consisting of authentic distortions to obtain a clear understanding about the status of state-of-the-art no-reference image quality assessment methods.

MDID: A multiply distorted image database for image quality assessment

Combining full-reference image visual quality metrics by neural network

This work addresses a possibility of using neural networks for the aforementioned purpose of assessing full-reference visual quality of images by using metric sets for images of the database TID2013 that are employed as the network inputs.

Full-Reference Image Quality Metrics Performance Evaluation Over Image Quality Databases

The visual information fidelity (VIF) quality metric has been found to have superior predictive capabilities to its counterparts and MS-SSIM, MSSIM and VIFP have also closer performances in terms of their correlation to the subjective human ratings, accuracy and monotonicity to the VIF model.



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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.


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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

  • H. SheikhA. Bovik
  • Computer Science
    2004 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 2004
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.

A universal image quality index

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.

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ISO 20462: a psychophysical image quality measurement standard

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Psycho-visual quality assessment of state-of-the-art denoising schemes

The quality of 7 state-of-the-art denoising schemes based on human visual perception are compared and attributes such as the noisiness, bluriness and artefacts present in the denoised images allowed to determine why people choose one filter over the other.

Evaluation of contrast sensitivity functions for the formulation of quality measures incorporated in halftoning algorithms

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