Abstract
In this paper, image contrast enhancement is achieved by combining together the local–global image statistics and multiscale morphological filtering (MMF). The proposed method has been executed on two different sets of images, and the result has been compared with that of some existing standard methods, namely histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE), and multiscale morphology in order to have an outlook on the relative performances. The experimental results manifest that the proposed method produced results superior to the methods compared.
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Gautam, G., Mukhopadhyay, S. (2018). Efficient Contrast Enhancement Based on Local–Global Image Statistics and Multiscale Morphological Filtering. In: Bhattacharyya, S., Chaki, N., Konar, D., Chakraborty, U., Singh, C. (eds) Advanced Computational and Communication Paradigms. Advances in Intelligent Systems and Computing, vol 706. Springer, Singapore. https://doi.org/10.1007/978-981-10-8237-5_22
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DOI: https://doi.org/10.1007/978-981-10-8237-5_22
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