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Image self-adapting method based on vision significance

A self-adaptive and remarkable technology, applied in image enhancement, image data processing, cathode ray tube indicator, etc., which can solve problems such as low resolution

Active Publication Date: 2009-08-19
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The smaller the screen size and lower the resolution of the smart mobile device, the more noticeable the distortion

Method used

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  • Image self-adapting method based on vision significance
  • Image self-adapting method based on vision significance
  • Image self-adapting method based on vision significance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] Embodiments of the image adaptive method based on visual salience of the present invention are described in detail as follows in conjunction with the accompanying drawings:

[0067] refer to figure 1 , shows the flow chart of the image adaptation method based on visual saliency of the present invention, which can realize the adaptation for image content in the environment of low resolution and small screen. It is programmed and implemented on a PC test platform with a CPU of 1.66GHz and a memory of 1024M, and some results during the processing are given. Its specific implementation steps are:

[0068] A. Calculate the energy of the original image: as Figure 2a , 2b , the original image shown in 2c, the original color image is converted into a grayscale image, and then the gradient of the grayscale image is calculated, and the size of each pixel gradient value is the energy value of each pixel corresponding to the original image;

[0069] B. Extract salient objects...

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Abstract

The invention discloses an image self-adaptive method based on visual saliency, comprising the steps as follows: firstly, the energy of an original image is calculated; secondly, a saliency object in the original image are extracted and the relative energy of the saliency object is strengthened; and thirdly, by utilizing a dynamic programming technique, the gaps with the lowest energy on the vertical and horizontal directions in the image are found out and eliminated so as to realize the image self-adaption. As the method eliminates the gaps with the lowest energy in the image, the whole energy loss of the image is the smallest; and as the relative energy of the saliency object is higher, the eliminated gaps can not pass through the saliency object, the saliency object can keep complete after the image self-adaption. Therefore, the method can minimize the image visual effect distortion in intelligent mobile equipment with low resolution and small screen and maintain the completeness of the saliency object, thereby providing a visual effect which is the same as that of display equipment with high resolution.

Description

technical field [0001] The invention relates to an image adaptive method based on visual saliency. This method is mainly considered from the perspective of the visual effect of image display, and aims to adaptively process the image suitable for the display environment of high-definition TV or wide-screen display, and can realize the low-resolution and small-screen environment of smart mobile devices. The overall distortion of the image content is minimized while maintaining the integrity of the salient content in the original image. Background technique [0002] With the rapid development of multimedia technology, it has become a reality to browse pictures and play TV programs in real time on mobile devices; with the increasing economic strength of people, more and more consumers have purchased smart mobile devices. Compared with ordinary mobile communication devices, the biggest advantage of smart mobile devices is that they integrate more application media. By using the...

Claims

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Application Information

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IPC IPC(8): G06T5/00G09G5/00
Inventor 刘志颜红波韩忠民沈礼权张兆杨
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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