Description: The ‘Scale Space’ is a conceptual and practical framework that allows for multiscale image analysis, facilitating the study of structures at different resolutions. This approach is fundamental in various disciplines, as it enables researchers and analysts to observe and understand complex phenomena that can vary significantly in size and detail. Scale Space is based on the idea that the characteristics of an image can be interpreted differently depending on the scale at which they are analyzed. For example, in image analysis, a structure may be visible at a macro scale, while finer details can only be appreciated at micro scales. This framework not only helps identify patterns and relationships in visual data but also allows for the integration of information from different scales, enriching the analysis and interpretation of results. Furthermore, Scale Space relies on advanced image processing techniques and algorithms that enable the manipulation and analysis of data at multiple resolution levels, making this approach a powerful tool in scientific research and industrial applications.
