Abstract:
When working with raw images obtained directly from the equipment matrix, specific
problems arise associated with a large dynamic range. The paper proposes a combined histogram correction
method that can significantly improve the contrast of such raw images with a large dynamic range. In the
combined method, soft clipping of highlights in the histogram is performed using a clustering algorithm
based on partitioning the feature space and gamma correction of the clipped area. The clustering algorithm
used manages to identify the cutoff point, both in the presence and absence of highlights in the image. The
method also produces weak edge accentuation based on Sobel filters. To improve the histogram, the
well-known Contrast Limited Adaptive Histogram Equalization method is used. In this case, a
combination of transformations with different mesh sizes is used, which allows one to achieve much
better results than when selecting one optimal transformation. These algorithms are described in detail
and illustrations for comparison are provided.
Citation:
M. A. Kazakov, “A combined method for histogram equalization
of high dynamic range images”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 6, 160–166
\Bibitem{Kaz23}
\by M.~A.~Kazakov
\paper A combined method for histogram equalization
of high dynamic range images
\jour News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences
\yr 2023
\issue 6
\pages 160--166
\mathnet{http://mi.mathnet.ru/izkab731}
\crossref{https://doi.org/10.35330/1991-6639-2023-6-116-160-166}
\elib{https://elibrary.ru/item.asp?id=https://www.elibrary.ru/item.asp?id=58804976}
\edn{https://elibrary.ru/MFQMMZ}