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A Calculation Method of Cumulative Signal-to-Noise Ratio of Image Based on Block Noise Variance Estimation

A noise variance estimation and calculation method technology, applied in calculation, image analysis, image data processing, etc., can solve problems such as rough division of uniform image intensity areas, unstable signal-to-noise ratio calculation results, and inaccurate image noise level estimation. , to achieve the effect of good monotony and applicability, and consistent visual experience

Inactive Publication Date: 2016-06-29
ZHEJIANG UNIV
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Problems solved by technology

This block method is rough for the division of areas with uniform image intensity, and is very sensitive to image content or some blurring, resulting in very unstable signal-to-noise ratio calculation results.
The inaccuracy of image noise level estimation severely limits the application of image signal-to-noise ratio evaluation algorithms

Method used

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  • A Calculation Method of Cumulative Signal-to-Noise Ratio of Image Based on Block Noise Variance Estimation
  • A Calculation Method of Cumulative Signal-to-Noise Ratio of Image Based on Block Noise Variance Estimation
  • A Calculation Method of Cumulative Signal-to-Noise Ratio of Image Based on Block Noise Variance Estimation

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Embodiment Construction

[0054] Algorithm flow chart of the present invention is as figure 1 shown.

[0055] by figure 2 The shown image is a target test legend, which is used to demonstrate the processing flow and result effectiveness of the algorithm of the present invention. In order to facilitate the display, in figure 2 A certain level of Gaussian white noise is added on the basis of the clear image, and the image to be calculated as the input signal-to-noise ratio, such as image 3 (a) shown.

[0056] Utilize the method of the present invention to process image, can at first obtain the result of watershed segmentation algorithm, display with the segmentation result of gray scale image, as image 3 As shown in (b), the segmentation method divides the image into several image blocks of equal size, mutual disjointness and uniform intensity. And after optimizing the processing of the affine reconstruction results, it can be obtained as image 3 (c) Affine reconstruction result plot shown in (...

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Abstract

The invention discloses a blocking noise variance estimation based image accumulation signal to noise ratio calculation method. By means of a watershed segmentation method in image segmentation processing, images are divided into blocks with uniform intensities, original image signal results are estimated through a blocking affine reconstruction method, meanwhile, border fuzzy processing is performed on affine reconstruction results to obtain optimal border fuzzy graphs, and signal to noise ratios of each section are accumulated with different weight factors in combination with noise splattering distribution to obtain an image accumulation signal to noise ratio index. The blocking noise variance estimation based image accumulation signal to noise ratio calculation method can be applied to fields such as image restoration, denoising and evaluation, and by means of the accumulation signal to noise ratio evaluation index, image qualities can be accurately evaluated.

Description

technical field [0001] The invention relates to computer image processing technology, in particular to an image accumulation signal-to-noise ratio calculation method based on block noise variance estimation. Background technique [0002] With the rapid development of digital multimedia technology, more and more digital images and videos are used in various fields of people's lives, and digitization has become an inevitable trend of future technological development. In the process of acquisition, compression, transmission, storage and processing of digital images, they will always be affected by various degradation factors, resulting in image degradation and degradation, seriously affecting the visual quality of images. The research on effective image quality evaluation methods has gradually become a research hotspot in digital image processing technology. [0003] The existing image quality evaluation methods are mainly divided into subjective evaluation methods and objecti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 崔光茫冯华君徐之海李奇赵巨峰
Owner ZHEJIANG UNIV
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