The document analyzes the effectiveness of various image quality assessment indices in detecting both structural and nonstructural distortions caused by processes such as acquisition, compression, and filtering. It categorizes different types of distortions, including noise and compression classes, and discusses the implications of these findings for image processing applications. The study emphasizes the importance of understanding how different distortions impact image quality and the human visual system.

1. Effectiveness of Image Quality Assessment Indexes on
Detection of Structural and Nonstructural Distortions
Michel Alves dos Santos ∗
January, 2014
Abstract
The main objective of this theme is to provide a study of effectiveness
of the main image quality indexes in relation to the detection of distor-
tions introduced after processes of acquisition, compression, filtering or
sampling, as well as introducing a range of "admissibility" of distortions
and degradation classes (like classes of noise, classes of blocking, classes
of compression, classes of fusion/blending, classes of watermarking, etc.).
Keywords: image processing, contrast distortion, image distortion, im-
age processing applications, loss of correlation, luminance distortion, im-
age quality index, distortion measurement, dynamic range, image quality,
mathematical models, human visual system, signal to noise ratio
∗Michel Alves dos Santos - Alves, M. - malves@cos.ufrj.br - http://www.michelalves.com. MSc. Candidate in
Computer Graphics, Image Processing and Computer Vision. http://www.lcg.ufrj.br - Laboratory of Computer
Graphics - LCG. Graduate Program in Systems Engineering and Computing (PESC). Alberto Luiz Coimbra In-
stitute for Graduate Studies and Research in Engineering - COPPE. Federal University of Rio de Janeiro (UFRJ -
http://www.ufrj.br), Brazil - Rio de Janeiro/RJ, Phone: (21) 8204-7102.
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2. Bibliography: Effectiveness of Image Quality Assessment Indexes on
Detection of Structural and Nonstructural Distortions
Michel Alves dos Santos
January, 2014
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