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Image zooming method

An image scaling and image technology, applied in image data processing, graphics and image conversion, instruments, etc.

Active Publication Date: 2017-03-22
HEBEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide an image zooming method, which is a fast zooming method based on threshold and probability, which overcomes the inability of the existing technology to meet the real-time image zooming speed while ensuring the image zooming effect Defects

Method used

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Examples

Experimental program
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Effect test

Embodiment 1

[0125] The training image library used in this embodiment is a total of 800 images from the 1st to the 800th of the MSRA image data set, and the energy vector distribution histogram and artificial threshold of each image are used as training data.

[0126] An image zooming method in this embodiment is a fast zooming method for images based on threshold and probability, which is divided into two processes, A. Radial basis function neural network model training process; B. The tested image that needs to be zoomed The scaling process, the specific steps are as follows:

[0127] A. The model training process of radial basis function neural network:

[0128] In the first step, input training images for preprocessing:

[0129] Input the color RGB image used for training through the USB interface, and input the color RGB image I for training tn Convert from RGB space to grayscale space to get grayscale image I gray_tn , the formula (1) used is as follows:

[0130] I gray_tn =0.2...

Embodiment 2

[0233] Except following difference, other is with embodiment 1:

[0234] (7.1) Delete operation:

[0235] The size of the tested color RGB image that needs to be scaled and the target image I o size for comparison, when w ts ts , perform the delete operation,

[0236] When the input needs to be scaled, the tested color RGB image and the target image I o The size of the two directions does not satisfy formula (13a), then the number of lines deleted in the horizontal direction N l The number of lines deleted in the vertical direction N w The calculation formula is as formula (14)

[0237] (7.2) Copy operation:

[0238] When the input needs to be scaled, the tested color RGB image and the target image I o The size of the two directions does not satisfy formula (15a), then the number of lines copied in the horizontal direction N l and the number of lines copied in the vertical direction N w The calculation formula is as formula (16),

[0239] (10.2) When the zoom ratio i...

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Abstract

The invention relates to an image zooming method, relating to a method of applying electronic equipment to carry out image zooming. The method is an image fast zooming method based on a threshold and a probability and is divided into two processes which comprise (A) a radial basis function neural network model training process and (B) the zooming process of a tested image with the need of zoom. According to the invention, a method of using a radial basis function neural network to carry out machine learning is used to calculate a threshold, the image with the need of zooming is divided into a protection area and a non protection area, the random zoom with the probability is used in zooming, and a defect that the guarantee of an image zoom effect and the satisfaction of a real-time image zoom speed can not be achieved at the same time in the prior art is overcome.

Description

technical field [0001] The technical solution of the present invention relates to a method for zooming an image by using an electronic device, specifically an image zooming method. Background technique [0002] With the development of digital video technology, the types of display devices with different resolutions and size ratios have proliferated, and the display ratios of various images and videos on the network are different. In order to make images and videos completely and properly displayed on different devices , image scaling becomes an urgent problem to be solved. [0003] Traditional image scaling methods include proportional scaling and image cropping. Among them, the proportional scaling method uses bilinear, bicubic interpolation or nearest neighbor method to directly scale the image to the required size according to the required ratio, which will cause severe deformation of the main body area due to stretching or compression; and The method of image cropping ...

Claims

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Application Information

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IPC IPC(8): G06T3/40
Inventor 于明侯骏腾刘依于洋师硕郭迎春
Owner HEBEI UNIV OF TECH
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