Abstract
Contrast is the key factor that determines the quality of the image and effectiveness of its visual perception. The purpose of this work is to improve the accuracy of quantifying the contrast of complex multi-element images using different metrics. To this end, this paper proposes a new approach to quickly quantifying the overall contrast of complex multi-element images. The proposed approach is based on assessing the distribution of brightness for the reference image, which has a maximum value of contrast for the used metric, and on the subsequent normalizing the magnitude of the given contrast estimate for the current image. Based on this approach, new definitions of incomplete integral contrast were proposed for linear and weighted contrast kernels. The proposed approach allows us to compare the contrast of different images based on estimates obtained using different metrics. The proposed approach provides improved the accuracy and reliability of the comparative analysis of the objective quality of different images using different metrics of contrast. The proposed approach allows us to more fully assess the relationship between various techniques of quantifying the overall contrast of images.
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Yelmanov, S., Romanyshyn, Y. (2021). A Quantitative Assessment of the Incomplete Integral Contrast for Complex Images. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing V. CSIT 2020. Advances in Intelligent Systems and Computing, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-63270-0_77
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