Laplacian Filtering in Spatial and Frequency Domains
Laplacian Filter In Spatial Domain Using Python
Laplacian Filter in Spatial Domain is used to enhance edges and detect fine details. It directly operates on pixel values of the image. In the spatial domain, Laplacian filtering involves convolving the image with a Laplacian kernel. The spatial domain approach directly operates on the pixel values of the image and applies the convolution operation using techniques such as sliding window or matrix multiplication.
Laplacian image is obtained after convolving the Laplacian kernel with the input image in spatial domain.
Original Image
+
Laplacian Image
= Enhanced Image
Laplacian Filtering in Frequency Domain
Laplacian filtering involves transforming the image into the frequency domain using techniques like the Fourier transform. The Laplacian filter is then applied to the frequency domain representation of the image. The filtered image is obtained by performing an inverse Fourier transform to return to the spatial domain.
Original Image-
Laplacian Image
= Enhanced Image
