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- W4365807112 abstract "While keeping all the significant signal features as much as possible, the removal of unnecessary noise from the images is the first goal of de-noising digital images. To eliminate the noise from digital images, different methods are used. Choosing the appropriate technique for the denoising process is the main part of de-noising. For image de-noising many techniques are proposed by researchers and they have their own demerits and merits. In this paper, a denoising technique is introduced using Dual-Tree Complex Wavelet Transform (DT-CWT) based implementation with the Bio Inspired Optimization Algorithm and Artificial Neural Network (ANN). Initially, various sub-bands are generated from the noisy image by applying DT-CWT. Then a trained ANN is applied on every sub-bands to obtain the noise-free wavelet coefficients. Threshold operation is performed on these output wavelet coefficients with Grey wolf optimization Algorithm (GWA) based optimized threshold value. By applying inverse DT-CWT the noise-free image can be obtained. This approach shows better performance when compared to other conventional methods." @default.
- W4365807112 created "2023-04-16" @default.
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- W4365807112 date "2023-01-01" @default.
- W4365807112 modified "2023-10-14" @default.
- W4365807112 title "Image Denoising Using DT-CWT Combined with ANN and Grey Wolf Optimization Algorithm" @default.
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- W4365807112 doi "https://doi.org/10.1007/978-981-19-7041-2_20" @default.
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