• Amit Kumar Rana
• KUMUD
• RAJESH MEHRA
• SHALLU

This paper presents a comparative analysis of curvelet and wavelet transforms using thresholding technique to denoise an image corrupted with different kinds of noise. Usually, the process of transmission, receiving, and coding leads to noise. Firstly, we discuss the digital implementation of two recently developed multi-scale transform: wavelet and curvelet transform. Curvelet transform is a newly class of multi-scale transform as compared to wavelet transform. The main aim of this paper is to analysis the noise removal using wavelet and curvelet transforms. Here, we apply these two transforms to restore the image from the noisy image and compare the special effects of denoising on that image. The experimental results show that the denoising method by curvelet transform is better as compared to wavelet transform as it gives low mean square error (MSE) and high peak signal to noise ratio (PSNR).

Wavelets, curvelets, denoising, image.

"A Comparative Analysis Of Wavelet And Curvelet Techniques For Noise Removal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 11, page no.615-618, November-2017, Available :http://www.jetir.org/papers/JETIR1711104.pdf

"A Comparative Analysis Of Wavelet And Curvelet Techniques For Noise Removal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 11, page no. pp615-618, November-2017, Available at : http://www.jetir.org/papers/JETIR1711104.pdf