DENOISING OF SAR IMAGES USING INTEGRATED REDUNDANT CURVELET TRANSFORMATION WITH EMD [ READ ]
A.Ravi, Dr. P.V.Naganjaneyulu, Dr.M.N. Giriprasad
As the progressive work is on noise removal from SAR (synthetic aperture images) images an efficient noise removal technique was proposed especially removing SPECKLE noise. This paper represents an improved denoising technique by redundant curvelet transformations for removing noise from SAR images. This improves information provided by the image and reducing noise rate in the same. This helps in preserving the images in multi resolution analysis and even filtering the curved architectures in the images. Various error calculation parameters were observing on these redundant curvelet transformation in combination with Empirical mode decomposition filtered image by indicating the best resultant value in the tabular form provided below in results. These observations were executed and results were simulated in MATLAB.
A.Ravi, Dr. P.V.Naganjaneyulu, Dr.M.N. Giriprasad
As the progressive work is on noise removal from SAR (synthetic aperture images) images an efficient noise removal technique was proposed especially removing SPECKLE noise. This paper represents an improved denoising technique by redundant curvelet transformations for removing noise from SAR images. This improves information provided by the image and reducing noise rate in the same. This helps in preserving the images in multi resolution analysis and even filtering the curved architectures in the images. Various error calculation parameters were observing on these redundant curvelet transformation in combination with Empirical mode decomposition filtered image by indicating the best resultant value in the tabular form provided below in results. These observations were executed and results were simulated in MATLAB.
