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Image denoising method based on n‑smoothlets

An image and image block technology, applied in the field of image denoising based on N-Smoothlets, can solve the problem of poor denoising method, and achieve the effect of reducing computational complexity and improving line singularity

Active Publication Date: 2018-01-30
SOUTHWEST PETROLEUM UNIV
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Problems solved by technology

[0036] The purpose of the present invention is to provide an image denoising method based on N-Smoothlets to solve the problem that the existing image denoising method is not effective

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  • Image denoising method based on n‑smoothlets
  • Image denoising method based on n‑smoothlets
  • Image denoising method based on n‑smoothlets

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Embodiment

[0143] Embodiment: Image denoising method based on N-Smoothlets

[0144] The image denoising algorithm based on multi-scale geometric analysis Smoothlet transform needs to change the weight λ many times to obtain the best denoising image, which seriously increases the computational complexity of the algorithm and limits its development. Therefore, this paper proposes an image denoising algorithm based on N-Smoothlets. This algorithm narrows down the search range of λ and reduces the computational complexity of the algorithm by seeking the relationship between the weight factor λ and the noise intensity in the image. At the same time, since N-Smoothlets has at most N reference lines in each macroblock to fit the edge, it can better describe the high-frequency information in the image.

[0145] 1 weight selection

[0146] In formula (1), Indicates the difference between the approximated image and the original image, therefore, the smaller the value, the better the approximatio...

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Abstract

The present invention relates to the field of image processing, specifically an image denoising method based on N-Smoothlets. The present invention utilizes the advantage that N-Smoothlets has better line singularity, and selects the weight factor λ in combination with the relationship between the weight factor and the noise intensity. Value, to achieve the best image denoising effect with the least amount of calculation, and reduce the high computational complexity caused by searching for the best λ. Finally, the experiment was carried out on the measured image, and compared with wavelet denoising and Smoothlet-based image denoising algorithms, the performance of the algorithm was verified from the PSNR value and subjective visual quality of the denoised image.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image denoising method based on N-Smoothlets. Background technique [0002] Generally, the image will be affected by electronic equipment, sensors, etc., so that various noises are superimposed on the image, which seriously affects the image quality. Among the common image denoising methods, wavelet analysis has been widely used because of its multi-resolution characteristics, which can effectively remove the noise in the image. However, wavelet denoising will affect the high-frequency information in the edge of the image, so that the edge of the image will be smooth and blurred after wavelet denoising, which reduces the effect of image denoising. The image denoising algorithm based on geometric multi-scale analysis has been widely used because the line singularity can better adapt to the edge in the image, and it can well protect the edge information of the image while removi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 段昶孙晓玲漆望月邱红兵李忠兵
Owner SOUTHWEST PETROLEUM UNIV
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