Abstract
The satellite images acquired from long distances are affected by different atmospheric disturbances such as noise and the image quality is degraded. The images thus require pre-processing to preserve the image quality for use in classification, fusion, segmentation etc. In the domain of image processing, analyzing the different noise types which affect the satellite images and also design the filter according to the affected noise is important. The existing filtering methods are capable of removing the noise in the image but is not much effective in preserving the image information such as edges, lines etc. This paper proposes a hybrid filtering technique for impulse noise removal. The hybrid filter comprises of a median filter which removes the impulse noise followed by a bilateral filter for edge preservation. The performance is studied based on the Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Feature Simillarity Index (FSIM), Structural Similarity Index (SSIM), Entropy and CPU time by comparing the results with existing denoising filters.
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Asokan, A., Anitha, J. (2019). Edge Preserved Satellite Image Denoising Using Median and Bilateral Filtering. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_59
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DOI: https://doi.org/10.1007/978-981-13-9181-1_59
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