Abstract
Noise is undesired or contaminated information present in images. During transmission, data may be affected due to noise and further processing of the same data does not produce good result. This affects the quality of the image which results in image blurring. Therefore, noise should be removed to get the clear information. In order to remove the noise, various denoising algorithms may be used. To preserve the details of the image, ridgelet transform uses hard thresholding algorithm. Ridgelet transform is used as it is concentrated near the edges of the image and it represents one-dimensional singularity in two-dimensional spaces. Wavelet is good in representing point singularities. When wavelet is linked with ridgelet, denoised image quality will be improved. Parameter like PSNR is calculated in order to measure the performance.
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Vetrivelan, P., Kandaswamy, A. (2014). Medical Image Denoising Using Wavelet-Based Ridgelet Transform. In: Sridhar, V., Sheshadri, H., Padma, M. (eds) Emerging Research in Electronics, Computer Science and Technology. Lecture Notes in Electrical Engineering, vol 248. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1157-0_25
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DOI: https://doi.org/10.1007/978-81-322-1157-0_25
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