Image Denoising Using Curvelet Transform Using Log Gabor Filter
In this paper, the authors propose a new method to reduce noise in digital image. Images corrupted by Gaussian Noise is still a classical problem. To reduce the noise or to improve the quality of image they have used two parameters, i.e., quantitative and qualitative. For quantity they will compare Peak Signal to Noise Ratio (PSNR). Higher the PSNR better the quality of the image. For quality they compare Visual effect of image. Image denoising is basic work for image processing, analysis and computer vision. The Curvelet transform is a higher dimensional generalization of the Wavelet transform designed to represent images at different scales and different angles.