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Publisher: SPIE
Languages: English
Types: Part of book or chapter of book
Subjects: UOW3

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Identifiers:doi:10.1117/12.838734
Sorting and searching operations used for the selection of test images strongly affect the results of image quality\ud investigations and require a high level of versatility. This paper describes the way that inherent image properties, which\ud are known to have a visual impact on the observer, can be used to provide support and an innovative answer to image\ud selection and classification. The selected image properties are intended to be comprehensive and to correlate with our\ud perception. Results from this work aim to lead to the definition of a set of universal scales of perceived image properties\ud that are relevant to image quality assessments.\ud The initial prototype built towards these objectives relies on global analysis of low-level image features. A\ud multidimensional system is built, based upon the global image features of: lightness, contrast, colorfulness, color\ud contrast, dominant hue(s) and busyness. The resulting feature metric values are compared against outcomes from\ud relevant psychophysical investigations to evaluate the success of the employed algorithms in deriving image features that\ud affect the perceived impression of the images.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • [9] Nixon M. S., Aguado A. S., “Feature Extraction and Image Processing”, 2nd ED., Academic Press, Oxford, England, UK, (2008).
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  • No similar publications.

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