MATLAB-based Image Super-resolution Technique
DOI:
https://doi.org/10.54097/z2b5dh91Keywords:
MATLAB; image super-resolution; deep learning; image processing.Abstract
This thesis provides an in-depth study of MATLAB-based image super-resolution techniques, covering the application of traditional methods (Fourier Transform, Wavelet Transform, Sparse Representation, Bicubic) and deep learning methods (SwinIR, NAFnet, Path-Restore). In the section on the background and significance of image super-resolution techniques, the wide range of applications of MATLAB in the field of image processing is explored. In the technical foundation section, the principles of image super-resolution technology are detailed, relevant image processing functions and tools in MATLAB are introduced, and the key steps of the technology are described. In the practical application, the comparative analysis of different methods is demonstrated through an example of image super-resolution in a real scene, including the effect diagram and MATLAB code. In the conclusion, the advantages and disadvantages of each method are summarized, which provides a certain reference for the future development of image super-resolution technology.
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