Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (11A): 221100153-8.doi: 10.11896/jsjkx.221100153

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Image Retargeting Method Based on Grids and Superpixels

CHEN Meiying, BI Xiuli, LIU Bo   

  1. Chongqing Key Laboratory of Image Cognition,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • Published:2023-11-09
  • About author:CHEN Meiying,born in 2001,bachelor.Her main research interest isimage processing.
    BI Xiuli,born in 1982,Ph.D,associate professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include image processing and multimedia information security.

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Abstract: Image is an important medium for communication between people.With the rapid development of information today,it is of great significance using image retargeting technology to make images adaptto a variety of device sizes.The grid-based image retargeting algorithm first generates a regular rectangular grid corresponding to the input image,and then determines the defor-mation degree of the grid by evaluating the weight of image pixels according to the image content in the grid.The global iteration of the image is carried out until the termination condition of image retargeting.However,such algorithms still have the problem of incomplete evaluation of image content,which leads to the distortion of the output image structure,and it is difficult to maintain the diagonal features and overall structure of the result image.In order to solve the above problems,this paper proposes an image retargeting method based on superpixels,gradients and saliency.Firstly,the input image is preprocessed by the superpixel me-thod,and then the superpixel block is used as the subsequent processing unit,and the image pixel weight evaluation method based on gradient and saliency is used to measure the weight of the superpixel output image,and an image retargeting weight heat map is output.Finally,the grid is iteratively optimized according to the retargeting weight heat map and realize the retargeting of the image.Experimental results show that the proposed method has certain advantages in the six no-reference image quality assessment indicators,and has certain advantages in semantic rationality,information accuracy and visual naturalness,and has great application value in the field of image retargeting.

Key words: Image processing, Image retargeting, Image significance detection, Superpixels

CLC Number: 

  • TP751
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