An Enhanced Type II Fuzzy Set Algorithm for Satellite Images Contrast Improvement

Manar Abdulkareem Al-Abaji, Mohammed Hazim Alkawaz

Abstract


Satellite images contain detailed information that is of great importance in the field of remote sensing. However, these images often suffer from low contrast due to numerous atmospheric obstructions. However, many methods have been developed to enhance these images but most of them have not achieved satisfactory results. Therefore, satellite imagery processing remains an active area of research. Hence, this research has proposed a modified type of II fuzzy set algorithm to improve the contrast of grayscale and color satellite images appropriately so as to maintain the overall brightness of the image and also give natural colors. The proposed algorithm employs a modified Hamacher t-conorm with a new lower and upper ranges. The resulting output is further processed based on sigmoid function and contrast stretching techniques to produce the final improved image. The proposed algorithm’s performance was assessed with natural degraded satellite images and compared with six other methods as well as the evaluation of the comparison’s outcomes was done using two metrics in addition to the processing time. It scored the optimum in both metrics, which obtain (20.907) in BRISQUE and (3.467) in NSS. The experimental results of the proposed algorithm demonstrated outstanding performance compared to the other methods as it produced images with clear details and natural colors without increasing image brightness.

Keywords


contrast enhancement; remote sensing; type-ii fuzzy; satellite images enhancement; sigmoid function

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References


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DOI: https://doi.org/10.32520/stmsi.v15i6.6474

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