High-pass kernels sharpen edges, while low-pass kernels (like imgaussfilt ) blur noise.
Where to Buy the "Practical Image and Video Processing" Book practical image and video processing using matlab pdf new
imread() : Imports an image file into the workspace as a matrix. imshow() : Renders the matrix visually on the screen. % Initialize video reader videoSource = VideoReader('traffic
% Initialize video reader videoSource = VideoReader('traffic.mp4'); % Create video writer object videoFrameRate = videoSource.FrameRate; videoTarget = VideoWriter('processed_traffic.avi'); open(videoTarget); % Process video frame by frame while hasFrame(videoSource) frame = readFrame(videoSource); % Example processing: Convert each frame to grayscale processedFrame = rgb2gray(frame); % Write the frame to the new file % Note: VideoWriter expects RGB, so replicate channels if grayscale writeVideo(videoTarget, cat(3, processedFrame, processedFrame, processedFrame)); end close(videoTarget); Use code with caution. Motion Detection and Background Subtraction Segmentation and Feature Extraction
Designing low-pass, high-pass, and band-pass filters to remove noise or enhance edges. 3. Segmentation and Feature Extraction