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Real image noise reduction method based on low-rank approximation

A low-rank approximation, real image technology, applied in the field of computational photography, can solve the problem of not taking into account the non-local self-similar prior of image noise characteristics, and achieve the effect of improving the restoration effect

Active Publication Date: 2019-07-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0006] Aiming at the problem that the existing noise reduction methods do not take into account the noise characteristics of the real image and the non-local self-similar prior in the image

Method used

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  • Real image noise reduction method based on low-rank approximation
  • Real image noise reduction method based on low-rank approximation
  • Real image noise reduction method based on low-rank approximation

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Embodiment Construction

[0064] In order to better illustrate the purpose and advantages of the present invention, the content of the invention will be further described below in conjunction with the accompanying drawings and examples.

[0065] A real image denoising method based on low-rank approximation disclosed in this embodiment is applied to the RGB real image captured by the camera. Because noise inevitably exists in the imaging system, an algorithm is used to perform denoising processing on the real image, and the obtained Restore the image. The flow chart of this embodiment is as follows figure 1 shown.

[0066] A real graph denoising method based on low-rank approximation disclosed in this embodiment includes the following steps:

[0067] Step 101: Establish an RGB real image noise reduction model, perform a block matching operation, and search for similar blocks for each local block to form a data matrix.

[0068] The RGB true noise map described in step 101 is simulated as Y=X+N, where ...

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Abstract

The invention discloses a real image noise reduction method based on low-rank approximation, and belongs to the field of computational photography. The implementation method comprises the following steps: establishing an RGB real image noise reduction model, carrying out block matching operation, searching a similar block for each local block, and forming a data matrix; calculating a weight matrixused for balancing real noise; performing low-rank approximation on each formed data matrix to obtain a denoised data matrix; and recovering the data matrix into blocks, and finally integrating the blocks into a noise-reduced recovered image, namely generating a high-quality real image noise-reduced recovered image. The noise reduction work of the real image can be completed with high quality, and the recovery effect of the real noise image is improved after the noise characteristics of the real image are fully considered. The method is suitable for multiple fields of medicine, military affairs, agriculture and the like.

Description

technical field [0001] The invention relates to a noise reduction method for RGB real noise images, in particular to a method capable of obtaining high-quality RGB images, and belongs to the field of computational photography. Background technique [0002] Noise is inevitable in the imaging system, which will damage the quality of the acquired image, and the noise reduction technology can restore the high-quality latent image from the noise-degraded image, which can effectively improve the image quality, improve the signal-to-noise ratio, and better to obtain the information carried by the original image. This technology has mature applications in medicine, military affairs, agriculture and other fields. [0003] As an important preprocessing method, image denoising algorithm has been extensively studied. In the early research, the noise was simulated as additive Gaussian noise, and the noise reduction algorithm was only designed for grayscale images, mainly including the ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/10024G06T5/70
Inventor 付莹郭悦楠黄华
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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