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@article{143823,
        author = {Disha P. Zanzad and Prof. Mrs. S. N. Rawat},
        title = {IMAGE DENOISING USING WAVELET AND CURVELET TRANSFORM},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {2},
        pages = {156-159},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143823},
        abstract = {The images usually bring different kinds of noises in process of receiving, coding and transmission. This paper describes a comparision of the discriminating power of the various multiresolution based thresholding techniques i.e. wavelet, Curvelet for image denoising. The Thecurvelet transform is new multiscale transform after 1999 that is based on wavelet transform, whose structural elements include the parameters of dimension and location, and orientation parameter more, which let curvelet transform has good orientation characteristic. Therefore, curvelet transform is superior to wavelet in the expression of image edge, such as geometry characteristic of curve and beeline, which has already obtained good research results in image denoising. This paper puts forward an improved method based on curvelet transform because certain regions of the image have the ringing and radial stripe after curvelet transform. The experimental results indicate that the improved curvelet transform has an abroad future for eliminating the noise of images. It suits not only the ordinary visual image, but also remote sensing image.},
        keywords = {Denoising, Curvelet Transform, Wavelet Transform, Orientation.},
        month = {},
        }