Image Filtering: Basics and Techniques

This lecture covers the fundamentals of image filtering, including linear and nonlinear filters, their applications in biological images, and techniques for artifact/noise removal, background subtraction, and feature enhancement. It explains spatial filtering, which manipulates pixel data to improve image aspects like contrast and feature enhancement. The lecture also discusses point operations for modifying pixel values without altering image structure, and provides examples of linear filters such as mean and Gaussian filters. Nonlinear filters like Gaussian and median kernels are explored, along with their applications. The instructor emphasizes the differences between linear and nonlinear filters, highlighting their advantages and performance characteristics.