Perona-Malik diffusion or anisotropic diffusion is a computer vision filtering technique that aims at reducing image noise without reducing the image’s quality in the process. This diffusion technique typically resembles the process that creates a scale space, where an image generates a parameterized family of successively more and more blurred images based on a diffusion process. Each of the resulting images in this filter is given as a convolution between the image and a 2D isotropic Gaussian filter. This diffusion is a linear and space invariant transformation of the original image. Anisotropic diffusion is a much generalized version of the diffusion process. It produces a family of parameterized images where each resulting image is a combination between a filter that depends on the content of the original image and the original image itself. This means that anisotropic diffusion is a linear and space invariant transformation of the original image