2015 |
K-means clustering for adaptive wavelet based image denoising Inproceedings Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in, pp. 134-137, 2015. |
2015 |
Agrawal, Utkarsh; Tiwary, Uma Shanker; Roy, Soumava Kumar; Prashanth, D S K-means clustering for adaptive wavelet based image denoising Inproceedings Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in, pp. 134-137, 2015. Links | BibTeX | Tags: adaptive soft thresholding, adaptive wavelet, Clustering algorithms, Discrete Wavelet Transform, Filtering, Gaussian noise, image denoising, image segmentation, inverse transforms, inverse wavelet transform, k-means clustering, K-Means Clustering Algorithm, k-means grouping statistical parameters, Noise, Noise measurement, pattern clustering, PSNR, Soft Thresholding, variable Gaussian noise, wavelet transforms @inproceedings{7164681, title = {K-means clustering for adaptive wavelet based image denoising}, author = {Utkarsh Agrawal and Uma Shanker Tiwary and Soumava Kumar Roy and D S Prashanth}, doi = {10.1109/ICACEA.2015.7164681}, year = {2015}, date = {2015-03-01}, booktitle = {Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in}, pages = {134-137}, keywords = {adaptive soft thresholding, adaptive wavelet, Clustering algorithms, Discrete Wavelet Transform, Filtering, Gaussian noise, image denoising, image segmentation, inverse transforms, inverse wavelet transform, k-means clustering, K-Means Clustering Algorithm, k-means grouping statistical parameters, Noise, Noise measurement, pattern clustering, PSNR, Soft Thresholding, variable Gaussian noise, wavelet transforms}, pubstate = {published}, tppubtype = {inproceedings} } |