Compressed sensing image reconstruction method combining bilateral total variation and non-local low-rank regularization
A bilateral full variation and image reconstruction technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of edge smoothing and information degradation of restored images, and achieve the effect of enhancing texture details
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[0064] The present invention will be further described below in conjunction with the accompanying drawings.
[0065] refer to Figure 1 ~ Figure 4 , a compressive sensing image reconstruction method combining bilateral full variation and non-local low-rank regularization, including the following steps:
[0066] Step 1, input the original test image x in the computer, and all test images are grayscale images of 256×256 pixels;
[0067] Test image used x ref figure 2 shown.
[0068] Step 2, set the sampling rate rates, and arrange the test images into a one-dimensional vector form x∈R N×1 , generating a sampling matrix Φ∈R M×N , to generate a CS measure by randomly sampling the Fourier transform coefficients of the input image, resulting in a measure y ∈ R M×1 ;
[0069] y=Φx
[0070] Sampling Rate N=256×256=65536, take 10% or 0.1 sampling rate, M=6553. A sampling matrix Φ is generated in a computer, and Φ is a part of a Fourier matrix.
[0071] Step 3, take the obta...
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