Method for reconstructing image based on blind compressed sensing module

Abstract

The invention discloses a method for reconstructing an image based on a blind compressed sensing module and mainly aims at solving problems that only sparse signals can be monitored by traditional compressed sensing, and the quality of the reconstructed image is poor. The method is realized by the following steps: (1) carrying out redundance transformation on an input image to obtain a redundance matrix; (2) carrying out compressed observation on the redundance matrix under an observation matrix; (3) updating a sparse matrix by an OMP (Orthogonal Matching Pursuit) algorithm in an adaptive way according to a compressed observation result; (4) updating a sparse base by a singular value decomposition method according to the updated sparse matrix; (5) multiplying the updated sparse matrix and the updated sparse base to obtain a reconstructed image redundance matrix; and (6) carrying out reverse redundance transformation on the reconstructed image redundance matrix to obtain a reconstructed image; and evaluating the reconstructed image by the peak signal-to-noise ratio of the image. The method has the advantages of high reconstructed image quality and great noise inhibiting effect and can be applied in image denoising and image compression.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a compressed sensing image reconstruction method, which can be used for image denoising and image compression. Background technique [0002] Compressed sensing theory can restore signals from a small amount of observation data, and has been applied to the field of image reconstruction. In practical applications, because the processed image signals often do not have sparsity, the traditional compressed sensing theory often needs Choose a fixed sparse base, the existing methods such as wavelet transform-based compressive sensing technology, discrete cosine transform-based compressive sensing technology, that is, first sparse under a fixed sparse base, and then observe the sparse signal, and observe the signal The more sparse the signal is, the better the effect of restoring and reconstructing the signal is, but this fixed sparse basis has a limited scope of app...

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Problems solved by technology

[0004] The purpose of the present invention is to propose an image reconstruction method based on blind compressive sensing to solve the problem that the signal must be sparse during compressed observation and the strict limitation of the initial basis during reconstruction, and directly use blind compressive sensing to image images containing complex images. Image reconstruction of information

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