• Yuriy Romanyshyn Institute of Telecommunications, Radioelectronics and Electronic Engineering (ITRE) of Lviv Polytechnic National University, Lviv, Ukraine. Head of the Department of Electronics and Computer Technologies (ECT),
  • Elena Yelmanova Institute of Telecommunications, Radioelectronics and Electronic Engineering (ITRE) of Lviv Polytechnic National University, Lviv, Ukraine PhD student of the Department of Electronics and Computer Technologies (ECT),




image quality, contrast metrics, no-reference, complex image, generalized contrast, contrast kernel, histogram


Background. Nowadays the task of automatically measuring of image quality in real time is extremely relevant for the vast majority of practical applications. No-reference quantitative assessment of image quality is one of the most pressing and difficult problems of image processing. Generalized contrast is the most important quantitative characteristic which determines the objective quality of the image. Currently, the development of new effective methods of no-reference measuring of generalized contrast for complex image in automatic mode with the level of computing costs, which are acceptable to implement the processing in real time, is one of the most urgent tasks of image preprocessing.
Objective. Development of new histogram-based method for no-reference measurement of generalized contrast of complex (multi-element) images based on the average contrast of image elements (objects and background) for different definitions of contrast kernel.
Methods. Analysis of known approaches to measurement of a local contrast of the image elements, of known methods of the quantitative assessment of generalized contrast of complex images as well as of the experimental research results for a series of complex real and test images allowed revealing inherent patterns (accordance to basic requirements to the definition of contrast, the nature and the dynamic of contrast changes at the linear transformations of the brightness scale), which are manifested depending on the use of the different definitions of the contrast kernels and the metrics of generalized contrast of
Results. No-reference contrast metrics for the histogram-based measuring of generalized contrast of complex images based on the average contrast of image elements for different definitions of contrast kernel is proposed.
Conclusions. Proposed no-reference metrics based on the average contrast of image elements for proposed contrast kernels allow providing accurate quantitative assessment (measurement) of generalized contrast of the real complex images and enable to evaluate (predict) with reasonable accuracy the perceived image quality at carrying out of subjective (qualitative) expert estimates.


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