An image processing method and device

An image processing and image block technology, applied in image communication, TV, color TV components and other directions, can solve the problem of lack of robustness, low reliability of estimation results, and inability to accurately estimate noise variance noise standard deviation at the same time and other problems, to achieve the effect of good image processing performance, accurate noise standard deviation or noise variance

Inactive Publication Date: 2007-08-15
WUXI ZGMICRO ELECTRONICS CO LTD
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AI Technical Summary

Problems solved by technology

For intra-frame noise estimation methods, most methods use the assumption that there are a certain proportion or a certain number of uniform blocks in the frame, and use the assumed proportion or number of blocks as a certain criterion for the final noise estimation. The accuracy of α depends largely on whether the assumed value of the ratio or the number of blocks is accurate. If the assumed value is too small, the estimated noise variance or noise standard deviation is also small; if the assumed value is too large, the estimated The noise variance or noise standard deviation is also too large; and no matter how the assumption is taken, the method cannot accurately estimate the noise variance or noise standard deviation in a smooth image and a detailed image at t

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  • An image processing method and device
  • An image processing method and device
  • An image processing method and device

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Embodiment Construction

[0058] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0059] 1. Obtain the noise estimate of the current image frame

[0060] In this embodiment, the noise estimation value may be obtained according to intra-frame estimation, inter-frame estimation, or a combination of the two, wherein:

[0061] A. Intra-frame estimation

[0062] In this embodiment, the image frame is divided into blocks, and it is assumed that each image block includes N pixels.

[0063] For a uniform block in each image block, each pixel in it satisfies the formula (1):

[0064] g(x)=μ+n(x) (1)

[0065] Among them, μ is the signal mean of the uniform block, n(x) is Gaussian white noise, n(x)~(0,σ 2 );

[0066] Then the intra-block mean of a uniform block can be expressed as:

[0067] μ g = 1 N Σ i = ...

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Abstract

The disclosed image process method for obtaining more accurate noise standard deviation or variance comprises: blocking the image frame to obtain the standard deviation or variance of small block, or, blocking the frame with its neighbor reference frame to obtain standard deviation or variance of every difference block; counting number of the block with same standard deviation or variance, and determining the noise standard deviation or variance according to the standard deviation or variance of block with the greatest number.

Description

technical field [0001] The present invention relates to an image processing method and device. Background technique [0002] Generally, video images inevitably contain noise. Noise not only affects image quality intuitively, but also greatly degrades the performance of many video image processing algorithms. Therefore, general video processing equipment should have noise removal devices. The performance of the denoising algorithm depends to a large extent on the accurate known or accurate estimation of the noise variance or noise standard deviation, but generally speaking, the noise variance or noise standard deviation cannot be accurately known, so a simple and reliable noise estimation algorithm is designed. And the denoising algorithm based on this is of great significance to video image processing. [0003] For noise estimation, existing video sequence noise estimation methods can be divided into two types: intra-frame estimation and inter-frame estimation. For intra...

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Application Information

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IPC IPC(8): H04N5/213H04N5/21H04N5/14
Inventor 梅大为邱嵩汪源
Owner WUXI ZGMICRO ELECTRONICS CO LTD
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