Image Denoising Using Curvelet Transform

Denoising techniques that are based on modifying the transform of an image are considered here. In these techniques, a reversible, linear transform (such as transforms discussed in Chapter 2) is used to map the noisy image into a set of transform coefficients, which are then filtered using a suitable thresholding technique. Fig. 4.1 shows a typical denoising system that uses transform techniques. The system performs three relatively straightforward operations: transformation, thresholding, and inverse transform. The transformation process packs as much information as possible into the smallest number of transform coefficients. Thresholding [8] can be accomplished by hard thresholding, which means setting to zero the elements whose absolute values are lower than the threshold, or by soft thresholding, which involves first setting to zero the elements whose absolute values are lower than the threshold and then scaling the nonzero coefficients toward zero. The inverse transform reconstructs the original image.