Image denoising method

Abstract

The invention discloses a remote sensing image denoising method. The method comprises the following steps of logarithm transformation, double-density dual-number complex wavelet decomposition, shrinkage coefficient calculation, layer-by-layer processing, double-density dual-number complex wavelet reconstruction, inverse-logarithm transformation and image output. Double-density double-tree complexwavelet transformation, the Bayesian theory and the quantum-derived idea are combined, and double-density double-tree complex wavelet transformation has translation invariance and the anti-aliasing characteristic, is more approximate to continuous wavelet transformation and has higher directivity, so that a mutual promotion effect is achieved after double-density double-tree complex wavelet transformation is combined with the quantum-derived method, the contradiction between spot removing smoothing and detail maintaining is better solved, the quality processed images is improved, an image speckle removing method is simple and effective, the image detail maintaining capability is high, a better visual effect is achieved, high-frequency signals and noise of the images are effectively distinguished, the self-adaptability of local filtering is enhanced, and image edge details are kept to a greater extent.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image denoising method. Background technique [0002] With the continuous development of science and technology, human cognition of remote sensing and the urgent need for scientific development have made our requirements for remote sensing higher and higher. Improving resolution and in-depth application have gradually become a major demand for the development of remote sensing science and technology. The current remote sensing image processing method has the problem that the image quality is not good enough, so it is necessary to study a new image processing method to improve the image resolution and image quality, and the quantum remote sensing image information processing is based on the related theories of quantum information and quantum mechanics. Studying images gives full play to the advantages of quantum computing and provides a new solution for fundame...

AI Technical Summary

Problems solved by technology

[0003] The traditional noise reduction method has a good processing effect on additive noise, but the remote sensing image contains a lot of coherent noise, the noise reduction performance of the traditional method is not strong, and it is easy to lose the relevant information in the original image

Images