In the deep space exploration

astronomical image acquisition

transmission and processing have always been the focus of research. To solve problems of slow convergence speed

poor denoising performance in compressed sensing iterative shrinkage-thresholding algorithm for image processing

an improved iterative shrinkage-thresholding astronomical image denoising and reconstruction algorithm with high performance is proposed. Firstly

the BB linear search stepsize of the classical steepest descent algorithm is used to accelerate the convergence speed of iterative shrinkage-thresholding algorithm; secondly

to further improve the reconstructed astronomical image quality

based on the classical VisuShrink shrinkage-threshold

a decreasing VisuShrink shrinkage-threshold is proposed to select the image information; since the pseudo-gibbs effect caused by threshold denoising method will appear in the process of image reconstruction

the cycle spinning method is finally employed to adjust the reconstructed image in each iteration. Multiple experimental results show that

compared with the traditional compressed sensing iterative shrinkage-thresholding algorithm

the algorithm proposed can not only obtain better denoising performance and faster convergence speed

but also effectively protect the astronomical image detail information

such as feature and texture. In addition

when compression sampling ratio is lower

the algorithm proposed also can obtain relatively higher peak signal to noise ratio and visual quality

proving the effectiveness of the algorithm proposed for astronomical image denoising.