UDC 004.932
DEVELOPMENT OF THE ALGORITHM FOR IMPROVING VIDEO IMAGES CONTRAST TO BE USED IN DIGITAL TELEVISION SYSTEMS
V. T. Dmitriev, Ph.D. (Tech.), associate professor, Radio Control and Communications Department, Head of the department, RSREU, Ryazan, Russia;
orcid.org/0000-0001-5521-6886, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A. A. Baukov, post-graduate student, RSREU, Ryazan, Russia;
orcid.org/0000-0002-0003-058X, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
The problem of improving the contrast of video images to be used in television systems is considered. Preliminary studies of known methods for solving this problem have been carried out. The aim of the work is to develop an algorithm for increasing contrast, in which the distortions inherent in known approaches are significantly reduced, and the restoration of color brightness characteristics of images exposed to undesirable phenomena that caused the weakening of contrast is also carried out. Statistical analysis of such parameters of low-contrast frame regions as intensity gradient vector modulus and pixel color saturation was performed using the method of minimizing objective function by the Nelder-Mead simplex algorithm. An algorithm for contrast enhancement is proposed, which differs from the known ones by adding stages of automatic assessment of necessary and sufficient degree of contrast increase in various frame areas, intensity correction and color saturation components with transition to HSI color space (Hue, Saturation, Intensity). A multi-criteria approach was used and the resulting quality criterion was introduced, including not only assessment of increase in contrast, but also reference indicators of image restoration, such as indices of structural similarity and mutual information. The authors have established that the proposed algorithm provides an increase in these criteria by 11...21 % and by 3...32 %, respectively, compared with known approaches with similar increase in contrast, and increase in the resulting quality indicator by 6...19 %.
Key words: : video processing, contrast, histogram equalization, approximation, objective function minimization, contrast enhancement degree, intensity, color saturation, multi-criteria approach.