Explore MATLAB source code curated for "空间域" with clean implementations, documentation, and examples.
This MATLAB implementation demonstrates the bilinear interpolation algorithm for spatial domain error concealment, featuring image restoration capabilities for damaged images through pixel value estimation from neighboring intact regions.
Performing Fast Fourier Transform on images, removing high-frequency information in the frequency domain, and applying inverse transform to spatial domain to eliminate image raster artifacts with implementation insights.
MATLAB Practice Program (Fuzzy Set Image Enhancement) The algorithm has multiple variations, but primarily consists of three key steps: 1. Design a membership function to transform the image from spatial domain to fuzzy set domain 2. Design a fuzzy enhancement operator to process the image in the fuzzy set domain 3. Transform the image back from fuzzy set domain to spatial domain using the membership function from step 1 This process is similar to the transformation-inverse transformation approach in frequency domain processing. The membership function and fuzzy enhancement operator used in this implementation are based on a classic paper in the field.
2013 CVPR Best Paper award-winning method that performs joint spatial and transform domain image denoising with simple implementation, achieving noise reduction performance comparable to BM3D algorithm through efficient domain fusion techniques.