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A Piecewise Linear Denoising Method of Signal Dependent Noise Based on Noise Level Function

A noise level, piecewise linear technology, applied in the field of image denoising, can solve the problem of image signals relying on noisy images, achieve good image effects, and improve the effect of filtering and denoising

Active Publication Date: 2020-08-04
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a signal-dependent noise piecewise linear denoising method based on the noise level function to solve the problem caused by the image signal-dependent noise in the traditional method and to achieve better denoising visualization effect

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  • A Piecewise Linear Denoising Method of Signal Dependent Noise Based on Noise Level Function
  • A Piecewise Linear Denoising Method of Signal Dependent Noise Based on Noise Level Function
  • A Piecewise Linear Denoising Method of Signal Dependent Noise Based on Noise Level Function

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Embodiment Construction

[0047] The present invention will be further described below.

[0048] The specific steps of a piecewise linear denoising method for signal-dependent noise based on the noise level function are as follows:

[0049] Step 1: Input a processed image containing signal-dependent noise. The resolution of the processed image is l·z; 1 Traversing the processed image for the step size, a 1 =3. Select M initial matching blocks, and the length and width of the initial matching blocks are both s 1 ,s 1 is an odd number (value 7 in this embodiment), The center point of the kth initial matching block is the processed image's row number The pixel where the columns intersect. k=1,2,...,M. means k divided by the remainder obtained; means k divided by Then round down the resulting value.

[0050] Step 2. Calculate the average value avg of each of the M initial matching blocks k As shown in formula (1), k=1, 2, . . . , M.

[0051]

[0052] In formula (1), e ijk is the p...

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Abstract

The invention discloses a signal-dependent noise segmental linear denoising method based on noise level function. In the prior art, the image fusion method for signal-dependent noise denoising requires multiple captures by cameras, which consumes a lot of manpower and calculations in practical applications, and consumes resources and time, so it cannot be used in practical applications. The invention is as follows: 1. Obtain and segment the noise level function curve of the processed image; 2. Divide the final matching block. 3. Further divide the search box in the final matching block. 4. Update the pixel at the center of the search box. The invention can accurately estimate the noise of the signal-dependent noise processed image, and clearly present the noise level function of the processed image. In addition, the present invention solves the problem that the traditional signal-dependent image denoising method cannot perform denoising with reference to the actual noise that changes with the gray level.

Description

technical field [0001] The invention belongs to the field of image denoising, and in particular relates to a signal-dependent noise segmental linear denoising method based on a noise level function. Background technique [0002] Images have become an important part of human's scientific and technological life. However, after the images are captured by actual cameras, there will be noise that will reduce the image quality. Noise from real cameras is better modeled as signal-dependent noise. Most of the denoising methods are simply denoising signal-independent noise or Gaussian noise, and there are very few denoising methods for signal-dependent noise. So far, the traditional signal-dependent-noise method still has some shortcomings and deficiencies. The image fusion method for signal-dependent noise denoising requires multiple captures by cameras, which consumes a lot of manpower and calculations in practical applications, and consumes resources and time, so it cannot be us...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 宋佳忠张钰李锦彧
Owner HANGZHOU DIANZI UNIV