This lecture covers the implementation of moving average filters, including recursive implementation in 1D and separable transfer functions. It also discusses symmetric exponential filters, exponential filtering implementation, and linear scale-space concepts. The instructor explains the Central-limit theorem, efficient Gaussian filtering, and the nomenclature of prototypical filters. The lecture concludes with a summary on discrete images, Fourier transforms, digital filtering, and popular image-processing filters.