Study and Comparison of Image Scaling Algorithms

Image scaling is a fundamental task in digital image processing and computer vision, which involves adjusting the size of an image to fit different display devices or storage needs. In this process, there is a trade-off between processing time and the smoothness and sharpness of the target. The purpose of image scaling algorithms is to solve the display of images on different resolutions. Current image scaling algorithms are not only traditional interpolation algorithms, but also algorithms centered on computer vision and content-aware techniques. This article aims at image scaling, and several common interpolation algorithms: nearest neighbor interpolation, bilinear interpolation, bicubic interpolation algorithm, and content-aware Seam Carving algorithm based on content-aware algorithms, and analyzes and compares the performance of these algorithms at multiple levels. Different interpolation formulas are summarised and simulation experiments are performed. Set to the same scaling ratio. Analyse and compare the details, sharpness, speed, and edges of the images of different algorithms after simulation. Discuss the advantages and disadvantages of their operation in different environments