De-noising Filters for TEM (Transmission Electron Microscopy) Image of Nanomaterials

TEM (Transmission Electron Microscopy) is an important morphological characterization tool for Nano-materials. Quite often a microscopy image gets corrupted by noise, which may arise in the process of acquiring the image, or during its transmission, or even during reproduction of the image. Removal of noise from an image is one of the most important tasks in image processing. Depending on the nature of the noise, such as additive or multiplicative type of noise, there are several approaches towards removing noise from an image. Image De-noising improves the quality of images acquired by optical, electro-optical or electronic microscopy. There are conventional methods like inverse filtering, Wiener filtering, Kalman filtering, Algebraic approach, etc., to restore the original object. The research paper aimed at describing &, comparing the usage of different types of filters namely Average Filter, Median Filter, and Wiener Filter for filtering amplifier noise present in a TEM Image of Nanomaterials. These filters are designed using a linear filtering Algorithm based on the sources of noise, pixel and the background of Image which depends on the substrate and Material present on TEM sample Grid.