Denoising and Reconstruction Method of CS High Noise Astronomical Image Combined with Fractional Total Variation

Abstract

The present invention proposes a CS high-noise astronomical image denoising and reconstruction method combined with fractional total variation. The multi-scale decomposition of high-resolution astronomical images under high-noise conditions by wavelet transform is used to obtain the curvelet coefficients; the iterative shrinkage threshold algorithm is used to iteratively update the curvelet coefficients to obtain image curvelet coefficients; the image curvelet coefficients are obtained by using the falling curvelet threshold operator The wave coefficient is used for noise reduction processing; the reconstructed astronomical image is obtained by using the curvelet inverse transform; the fractional total variation method is used to adjust the characteristics of the reconstructed astronomical image to obtain the adjusted reconstructed image; the iteration stop condition is judged. The invention effectively improves the denoising capability of high-resolution astronomical images under high-noise conditions, solves the problem of de-noising and reconstruction of astronomical images under high-noise conditions in deep space exploration, and has simple implementation and strong robustness.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a CS high-noise astronomical image denoising and reconstruction method combined with fractional total variation, which combines compressed sensing (CS) and total variation to perform denoising processing on astronomical images to achieve high Fast denoising and reconstruction of noisy astronomical images, especially the fast denoising ability of high-resolution astronomical images under high noise conditions. Background technique [0002] With the continuous development of aerospace technology, deep space exploration has become more and more important. In order to actively develop and utilize space resources, countries all over the world are making active efforts to explore extraterrestrial bodies, space resources, etc., and have formulated long-term deep space exploration plans. Astronomical images are of great significance in deep space exploration. From the high-reso...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the technical problem of poor reconstruction quality when existing CS reconstruction methods reconstruct high-noise astronomical images under high-noise conditions, the present invention proposes a CS high-noise astronomical image denoising and reconstruction method combined with fractional total variation. In the stage, an adaptive filter operator is introduced to perform sparse transformation and denoising processing on high-noise astronomical images; then, the fractional total variation method is introduced into the iterative shrinkage threshold algorithm in CS, and in each iteration, the fractional The first-order total variation method is used to adjust the reconstructed astronomical image, which effectively improves the reconstruction quality of the astronomical image, and finally realizes the high-quality reconstruction of the high-resolution astronomical image under the condition of high noise.

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