Multispectral image reconstruction method based on dual-tree complex wavelet transformation

Abstract

The invention discloses a multispectral image reconstruction method based on dual-tree complex wavelet transformation and aims at solving the problems of unideal reconstruction effect and low reconstruction speed in the existing multispectral image reconstruction technology. The multispectral image reconstruction method based on dual-tree complex wavelet transformation comprises the steps of (1) obtaining an aliased spectral image, (2) performing data initialization, (3) performing noise reduction processing, (4) determining whether the continuing condition of a current estimated value is satisfied, (5) obtaining next estimated value of the current estimated value of image reconstruction, (6) determining whether the continuing condition of the next estimated value of the current estimated value is satisfied, (7) updating the estimated value, and (8) determining whether an end condition is satisfied. The multispectral image reconstruction method based on dual-tree complex wavelet transformation has the advantages that dual-tree complex wavelet transformation is adopted to realize noise reduction processing on the image, and a good multispectral image reconstruction result and a relatively high multispectral image reconstruction seed can be obtained in the reconstruction process of compressive spectral imaging.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a multispectral image reconstruction method based on dual-tree complex wavelet transform in the technical field of compressed spectral imaging. The invention can be used for reconstruction of multi-spectral images, improves image reconstruction quality, and improves reconstruction speed. Background technique [0002] In the field of compressed spectral imaging technology, the collected multispectral image data is far less than the original multispectral image data, and the reconstruction process of the multispectral image is transformed into an inverse problem based on compressive sensing theory for solution. [0003] Jos′e M.Bioucas-Dias, M′ario A.T.Figueiredo, in the literature "A New TwIST:Two-Step Iterative Shrinkage / Thresholding Algorithms for Image Restoration" (IEEE Transactions on Image processing,2007,16(12):2992- 3004) proposed to update the current value by t...

AI Technical Summary

Problems solved by technology

There are still some deficiencies in this method when performing multispectral image reconstruction: first, the computational complexity of total variation denoising is high, there is no fast algorithm, and the data volume of multispectral images is large, which makes the reconstruction speed of this method relatively slow. slow

[0005] In summary, although the existing methods can reconstruct multispectral images, they do not take into account the defects of the denoising methods used, which makes the reconstruction speed slower and it is difficult to obtain better reconstructed images

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