Abstract
Intensity transformation is one of the basic approaches to enhance the image. However, known methods of intensity transformation have several disadvantages which significantly limit their use for image processing in automatic mode. In this paper, the problem of improving the efficiency of the intensity transformation of complex images in the automatic mode was considered. A new approach to the intensity transformation was proposed based on equalizing the distribution density of contrast in an image. The distribution of contrast is estimated based on bivariate distribution and brightness increments for pairs of pixels in the image. A new generalized description of the intensity transformation based on the joint distribution of brightness was proposed. It was shown that the traditional definition of histogram equalization is a particular case of the proposed generalized description. A new technique of parameter-free intensity transformation was proposed based on equalizing the distribution density of contrast in an image. The proposed technique provides an effective enhance the contrast of complex images without the appearance of unwanted artifacts has several advantages to the well-known histogram equalization technique. The results of experimental research confirm the effectiveness of the proposed approach to enhance images in automatic mode.
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Yelmanov, S., Romanyshyn, Y. (2020). A New Approach to Image Intensity Transformation Based on Equalizing the Distribution Density of Contrast. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing IV. CSIT 2019. Advances in Intelligent Systems and Computing, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-33695-0_28
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DOI: https://doi.org/10.1007/978-3-030-33695-0_28
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