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Wavelet soft threshold image denoising method based on Renyi entropy

A wavelet soft threshold, image technology, applied in image enhancement, image analysis, image data processing and other directions, can solve the problem of no corresponding existing technology and so on

Active Publication Date: 2019-10-18
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0008] However, based on wavelet transform and Renyi entropy combined with denoising, there is no corresponding prior art

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  • Wavelet soft threshold image denoising method based on Renyi entropy
  • Wavelet soft threshold image denoising method based on Renyi entropy
  • Wavelet soft threshold image denoising method based on Renyi entropy

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specific Embodiment

[0107] This embodiment describes the specific implementation of a wavelet soft threshold image denoising method based on Renyi entropy according to the present invention, and its process is as follows figure 1 shown.

[0108] This embodiment describes the specific implementation of applying a wavelet soft threshold image denoising method based on Renyi entropy according to the present invention to perform denoising processing on underwater images.

[0109] After reading in a color noisy image, first decompose the image into three sub-images I R ,I G ,I B . For each sub-image, through the two-dimensional discrete wavelet transform (2-D DWT), using bior2.2 wavelet, the number of decomposition layers is selected as 3, and the coefficient matrix C_R with the row number of 1 for the wavelet decomposition of the noisy image is respectively obtained , C_G, C_B, where the coefficient matrix is ​​expanded in columns according to the approximate coefficients and detail coefficients ...

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Abstract

The invention relates to a wavelet soft threshold image denoising method based on Renyi entropy, and belongs to the technical field of image denoising and wavelet transform. The method comprises the following steps: 1, splitting an RGB color image into three sub-images with a single color; 2, performing discrete wavelet transform on the three sub-images output in the step 1, and outputting high-frequency coefficients of the Jth layer, the J-1 layer and the J-2 layer; wherein the wavelet generating function is one of bior2.2 and sym4, and the wavelet generating function is one of bior2.2 and sym4; 3, taking interval boundaries corresponding to the two-dimensional Renyi entropy values of the high-frequency coefficients of the Jth layer, the J-1 layer and the J-2 layer output in the step 2 asoptimal segmentation thresholds; 4, adjusting thresholds of the Jth layer, constructing the J-1 layer and the J-2 layer, and performing wavelet denoising on the high-frequency coefficient of the Jthlayer with the adjusting thresholds as soft thresholds; and reconstructing the image to complete two-dimensional discrete wavelet inverse transformation to obtain a denoised image. According to the method, the point noise in the image signal can be effectively separated from the image signal.

Description

technical field [0001] The invention relates to a wavelet soft threshold image denoising method based on Renyi entropy, which belongs to the technical field of image denoising and wavelet transform. Background technique [0002] Light waves will rapidly attenuate due to absorption in water, so the traditional optical image capture method is often blurred when shooting underwater targets. Another commonly used underwater imaging method: sonar imaging, due to the low resolution and serious noise problems during imaging, it is difficult to identify underwater targets. [0003] Among many denoising algorithms, the wavelet denoising algorithm can effectively remove noise while retaining edge information, and the denoising effect is better. Wavelet transform is widely used in the field of image denoising. The wavelet threshold denoising algorithm has been comprehensively and extensively studied because of its short time and good effect. [0004] Denoising using wavelet transform...

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Application Information

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IPC IPC(8): G06T5/00G06T7/136
CPCG06T7/136G06T5/70
Inventor 张延军李慧琦张超赵宇娇
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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