Noise Removal Technique Using Curvelet Transform and Filtering approach of Satellite Images


  • R.Swaminathan R.Swaminathan is with the department of Electronics & Communication Engineering ,Galgotias University,Greater Noida, India
  • Himanshu Agarwal Himanshu Agarwal is a MTECH student in the department of ECE,Galgotias University
  • Manoj Wadhwa Manoj Wadhwa is with the department of CSE, Echelon Institute of technology, Faridabad


Curvelet, Gabor, Unsharp, Noise,Edge.


Noise removal from Satellite Images is a major area of research and there are many techniques used for this
process. Due to the presence of noise the images are corrupted and the information present in the image is not clearly
visible.Many transform techniques and filters were used for removal of noise and enhancement of images.In this paper we
use Curvelet transform which is a multiscale directional transform that allows an almost optimal nonadaptive sparse
representation of the object with edges. Curvelet transform has the advantage of handling curve discontinuities very well.
Curvelet transform is used in this paper to remove the noise present in the image and also to improve the edges. Filters like
Gabor filter and Unsharp filter is also used along with curvelet to remove the noise and to increase the sharpness of the
image. Quantitative parameters like PSNR,Entropy is used to measure the quality of the image.The results shows the
superiority of the proposed method.



How to Cite

R.Swaminathan, Himanshu Agarwal, & Manoj Wadhwa. (2015). Noise Removal Technique Using Curvelet Transform and Filtering approach of Satellite Images. International Journal of Advance Engineering and Research Development (IJAERD), 2(4), 95–101. Retrieved from