Image reconstruction method based on neighborhood pixel jump distribution function extraction

A distribution function and image reconstruction technology, which is applied in image enhancement, image data processing, 2D image generation, etc., can solve the problem of low regression degree

Inactive Publication Date: 2010-03-10
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0009] The purpose of the present invention is to overcome the shortcoming of the low regression degree in the existing image neighborhood jump distribution function regression technology,

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  • Image reconstruction method based on neighborhood pixel jump distribution function extraction
  • Image reconstruction method based on neighborhood pixel jump distribution function extraction
  • Image reconstruction method based on neighborhood pixel jump distribution function extraction

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Embodiment Construction

[0062] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the protection scope of the present invention is not limited to the scope described in the examples.

[0063] Use the present invention to carry out super-resolution image reconstruction to the Lena image, and input the pixel information of the image into the computer in the form of a matrix, and img(i, j) corresponds to the i-th row in the image array, the image pixel in the j-th column value. The image width is width (in pixels, width is 512 in this example), and the height is height (in pixels, height is 512 in this example). figure 1 Among them, img(i, j) is the image information input in the form of matrix, ΔI is the neighborhood jump value, sum`(ΔI) is the statistical array of neighborhood jump values, and the length is 511. The corresponding relationship between the elements in sum`(ΔI) and the image jump value ΔI is: the c...

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Abstract

The invention discloses an image reconstruction method based on neighborhood pixel jump distribution function extraction. The method includes five steps of image neighborhood distribution statistics,function regression, regression effect evaluation, function extraction and super-resolution image reconstruction, wherein the image neighborhood distribution statistics counts the jump values of adjacent pixels in images and carries out normalization treatment on the jump values; the function regression firstly uses the digital image imaging principle to obtain the model of the image neighborhoodpixel jump function, and then according to the distribution situation of adjacent pixels, adopts a non-linear regression method to calculate and obtain the parameter of the function; and the regression effect evaluation compares the accuracy of functions by taking a deviated energy value as a standard and extracts the optimal jump distribution function according to the accuracy. The invention provides a reasonable function model and improves the accuracy of extraction result. By applying the extracted function result in the super-resolution image reconstruction field, the method achieves better result than the traditional method.

Description

technical field [0001] The invention relates to an image reconstruction method based on the extraction of neighborhood pixel jump distribution functions, in particular to a digital image reconstruction method obtained by sampling and quantizing digital imaging equipment. Background technique [0002] Digital image processing refers to the use of computers to process digital images for various purposes. The purpose of early image processing is to improve the quality of the image, and it takes people as objects to improve people's visual effects. In image processing, the input is an image with poor quality, and the output is an improved image. The commonly used image processing methods include enhancement, restoration, encoding, compression, etc. There is another type of image processing that takes computers as objects, and the purpose of processing is to enable computers or machines to automatically identify targets, which is called image recognition. The input of the image...

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Application Information

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IPC IPC(8): G06T11/00G06T5/00
Inventor 冯久超谭啸
Owner SOUTH CHINA UNIV OF TECH
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