Morphological Processing is a broad set of non-linear image processing operations that process images based on shapes. It pursues the goals of removing imperfections in the image by accounting for the form and structure of the image. Morphological operations rely only on the relative ordering of pixel values, not on their numerical values, and therefore are specifically better suited to the processing of binary images. Morphological techniques probe an image with a small shape or template called a structuring element. These are applied to an input image, creating an output image of the same size. In a morphological operation, the value of each pixel in the output image is based on a comparison of the corresponding pixel in the input image with its neighbours. Some operations test whether the element ‘fits’ within the neighbourhood, while others test whether it ‘hits’ or intersects the neighbourhood. By choosing the size and shape of the neighbourhood, you can construct a morphological operation that is sensitive to specific shapes in the input image.
Geometric image modification involves operations over an image in which an image can be spatially translated, scaled in size, rotated, non-linearly warped or viewed from a different perspective. Geometric transformations are widely used for image registration and the removal of geometric distortion. Common applications are in computer graphics that include construction of mosaics, geographical mapping, stereo and video.
