Description: Spatial filtering is a technique used in image processing that applies a filter directly in the spatial domain, that is, in the two-dimensional representation of the image. This technique allows for modifying or enhancing the visual characteristics of an image by manipulating the pixel values that compose it. Spatial filters can be of different types, such as smoothing filters, which reduce noise and fine details, or enhancement filters, which highlight edges and specific features. The application of these filters is performed through convolution, where a mask or kernel is moved over the image, performing calculations at each position to generate a new filtered image. This technique is fundamental in various areas such as computer graphics, image processing, and computer vision, as it allows for improving the visual quality of images and facilitating the extraction of relevant information. Additionally, spatial filtering is a key component in training convolutional neural networks, where filters are used to learn hierarchical features of images, resulting in better performance in classification and object detection tasks.
