Abstract
The quality of the image plays a vital role in numerous image processing applications such as medical image analysis, pattern recognition, satellite image processing, etc. One of the most important noises that affect the quality of the image is impulse noise. This noise alters the value of the pixels to either extreme. An efficient noise reduction algorithm is required to improve the quality of the image by detecting the noisy pixels and then replacing it with the appropriate value. The algorithm should have high noise reduction efficiency and computational efficiency especially when dealing with high noise density images. This paper proposes an improved algorithm which detects the noisy pixels using Cloud Model method and replaces the value of the corrupted pixel by Cloud Model Average (CMA) method, which improves computational efficiency by 2.94 % without compromising the noise reduction efficiency compared to the existing methods in the literature.
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Kumar, S.V., Nagaraju, C. (2017). Removal of High Density Salt and Pepper Noise from the Image Using CMA. In: Attele, K., Kumar, A., Sankar, V., Rao, N., Sarma, T. (eds) Emerging Trends in Electrical, Communications and Information Technologies. Lecture Notes in Electrical Engineering, vol 394. Springer, Singapore. https://doi.org/10.1007/978-981-10-1540-3_11
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DOI: https://doi.org/10.1007/978-981-10-1540-3_11
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