A Super-resolution Reconstruction Method Based on Image Edge Preserving Adaptive Decomposition

Abstract

The invention discloses an image super-resolution reconstruction method. The method includes two parts: 1. Adaptive decomposition of the image. The so-called self-adaptation here refers to the self-adaptive drive decomposition process of the image data. 2. Perform super-resolution amplification on the basis of image adaptive decomposition. On the basis of adaptively decomposing the image into low-frequency information and high-frequency information, a Gaussian mixture model is used as a priori model in the high-frequency part for super-resolution amplification, and spline interpolation is used in the low-frequency part, and finally superimposed. The invention can realize high-quality enlargement of images.

Description

A super-resolution reconstruction method based on image edge-preserving adaptive decomposition Technical field The present invention relates to the technical field of image processing, especially a kind of single frame based on image edge preservation adaptive decomposition Image super-resolution reconstruction method. Background technique In recent years, image super-resolution method has been the focus of research, in image tracking, image segmentation and video retrieval and other fields are closely related, so the research on image super-resolution algorithms is of great significance, especially in the set It is of great significance in the acquisition of field emission scanning electron microscopy images. Therefore, an adaptive decomposition based on image edge preservation is developed The super-resolution reconstruction algorithm has become one of the central tasks of integrated circuit field emission scanning electron microscope acquisition. Existing method ...

AI Technical Summary

Problems solved by technology

The components are mixed, and the probability and statistics model established is not scientific

Images