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Image scaling processing method based on Newton three-association continuous fraction mixed rational interpolation

A processing method and image scaling technology, which can be used in image data processing, graphic image conversion, instruments, etc., and can solve problems such as distortion, blurring, and aliasing.

Active Publication Date: 2020-01-21
HEFEI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, its texture and edge processing is not satisfactory, and when the magnification factor is high, distortion, blurring, and jaggedness will appear

Method used

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  • Image scaling processing method based on Newton three-association continuous fraction mixed rational interpolation
  • Image scaling processing method based on Newton three-association continuous fraction mixed rational interpolation
  • Image scaling processing method based on Newton three-association continuous fraction mixed rational interpolation

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0106] Construction of mixed rational interpolation of Newton's triple-connection continued fraction:

[0107] 1. Construction of mixed rational interpolation of Newton's triple-correlation continued fraction:

[0108] First construct a new binary mixed rational interpolation. The advantage of the continued fraction is that it is simple in structure and easy to calculate; only need to calculate the corresponding difference based on the interpolation method.

[0109] given the true set of a set of points

[0110]

[0111] and a function

[0112] f(x)∈C 3[n / 3]+3 [a, b] (3.1.2) It is well known that it can be extended to the following Newton interpolation with remainder

[0113]

[0114] when ω 0 (x)=1, ω i (x)=(x-x 0 )(x-x 1 )…(x-x i-1 ), i=1, 2, ..., 3[n / 3]+2, and f[x 0 , x 1 ,...,x i ] means different difference f(x) in point set x 0 , x 1 ,...,x i definition

[0115]

[0116] suppose

[0117]

[0118] then P 3[n / 3]+2 (x) is a polynomial coefficien...

Embodiment 2

[0195] As a comparison, Example 2 provides three traditional linear interpolation methods

[0196] 1. Nearest neighbor interpolation method

[0197] As an interpolation method with the most convenient implementation, the simplest algorithm and the fastest calculation speed.

[0198] Can be expressed as a polynomial:

[0199] g(x)=f(x k )(x k-1 +x k ) / 2k +x k+1 ) / 2

[0200] (2.2.1)

[0201] That is, the kernel function of the nearest neighbor interpolation is

[0202]

[0203] When the original image is doubled in full scale, the (0,0) pixel in the enlarged target image corresponds to the (0,0) pixel in the original image; the (0,1) pixel corresponds to (0,0.5) in the original image Pixel, which can be approximated as (0,0) or (0,1); (0,2) pixel corresponds to (0,1) pixel in the original image; (1,0) pixel corresponds to (0.5,0) in the original image ) pixels, which can be approximated as (0,0) or (1,0); (2,0) pixels correspond to (1,0) pixels in the original image....

Embodiment 3

[0219] Utilize the interpolation method that embodiment 1 and 2 provides to realize image scaling processing, the flow chart of processing is as follows figure 1 As shown, the specific steps are:

[0220] ①. Read an input image that needs to be scaled;

[0221] ②. Segment the image matrix into multiple small matrices with three rows and three columns;

[0222] ③. Process the edge matrix of the image: move forward enough rows or columns to make up three rows and three columns;

[0223] 4., carry out interpolation (the interpolation method that embodiment 1 and 2 provides) calculation to all small matrices respectively by loop control;

[0224] ⑤. Generate a new image matrix and display the processing results

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Abstract

The invention discloses an image scaling processing method based on Newton three-association continuous fraction mixed rational interpolation, and belongs to the technical field of graphic image processing. Reading an input image which needs to be zoomed; segmenting the image matrix into a plurality of small matrixes with three rows and three columns; an edge matrix of the image is processed, wherein enough row number or column number is moved forwards, and three rows and three columns are adjusted; performing interpolation calculation on all the small matrixes through loop control; and generating a new image matrix, and displaying a processing result. A zooming result of a traditional linear method is obviously fuzzy at details, and a mosaic phenomenon exists when the magnification timesare large. Compared with a traditional method, the edge and texture of the method are obviously improved, and a good visual effect is guaranteed. Through clear scaling result comparison, the progressof nonlinear scaling in the aspect of visual effect compared with traditional scaling is highlighted, the feasibility of nonlinear scaling is proved, and the texture effect of the image can be well kept through image scaling.

Description

technical field [0001] The invention belongs to the technical field of graphics and image processing, and in particular relates to an image scaling processing method based on Newton's triple-correlation continued fraction mixed rational interpolation. Background technique [0002] The essence of image scaling is the resampling of images, which has an unshakable position in image processing technology and is used to realize the function of changing image resolution and size. The interpolation algorithm is the soul of image scaling. If the effect is too poor or the running speed is too slow, it will greatly affect the entire scaling result, resulting in image distortion, blur and even mosaic phenomenon. With people's higher and higher requirements for image quality, the traditional scaling technology is facing severe challenges. [0003] The linear interpolation method has been widely used in image scaling technology, and has the advantages of simple algorithm and fast operat...

Claims

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Application Information

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IPC IPC(8): G06T3/40
CPCG06T3/40G06T3/4007G06T3/4023Y02D10/00
Inventor 邹乐王晓峰宋良图张琛唐超黄前静
Owner HEFEI UNIV
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