Method for super-resolution of image and video based on fractal analysis, and method for enhancing super-resolution of image and video

Abstract

The invention discloses a method for super-resolution of images and videos based on a fractal analysis, and a method for enhancing the super-resolution of the images and videos. The methods comprise the following steps: reading an image or a frame in a video, recording as I, calculating a gradient Gradori of the I; performing a super-resolution process on the I based on interpolation to obtain an estimated value H' of the high-definition image; calculating a gradient Gradest of the H'; calculating fractal dimension Dori and Dest, and fractal length Lori and Lest of corresponding pixel of the I and H' through the Gradori and the Gradest, respectively; reestimating the gradient GradH of the high-definition image according to scale invariance of the fractal dimensions and the fractal lengths; and reestimating the high-definition image, with the H' and the GradH as restrictions. The methods uses pixel of the image as a fractal set and the gradient corresponding to the pixel as a measure of the fractal set, and local fractal dimensions and local fractal lengths of the image are calculated. According to the scale invariance of the fractal dimensions, a super-resolution problem is restricted. Through bringing in a restriction of the scale invariance of the fractal lengths, the methods can be used in image quality enhancement of images and videos, and especially in texture enhancement.

Description

technical field [0001] The invention relates to a system in the technical field of image and video processing, in particular to an image and video super-resolution and enhancement method based on fractal analysis. Background technique [0002] With the advancement of technology, more and more information with images and videos as the carrier is presented to us in digital form, such as movies, TV shows, games, photos, etc., bringing fun and spiritual enjoyment to our lives. However, compared with traditional film-based imaging methods, objectively, digital imaging technology has a decline in image resolution. Not only that, but due to interference in the shooting process, limitation of transmission bandwidth, backwardness of imaging equipment, and poor storage, the quality of images and videos degrades during the display process, and the visual experience of the human eye is also affected accordingly. Among these adverse effects, the reduction of image resolution has a parti...

AI Technical Summary

Problems solved by technology

However, the problem with this type of algorithm is that there is no basis for the parameter setting in the algorithm, and it often needs manual adjustment or training based on statistical methods.

In addition, this type of method has no constraints on the brightness of the image, resulting in the danger of over-enhancement of the processing results.

[0004] The above two types of methods have the shortcomings of lack of theoretical basis and no good model as the basis

Images