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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Danfeng Zhao,Bo Wang.Optimized Content-Aware Image Resizing with Merging andImproved Importance Diffusion[J].Journal of Harbin Institute Of Technology(New Series),2015,22(2):67-73.DOI:10.11916/j.issn.1005-9113.2015.02.010.
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Optimized Content-Aware Image Resizing with Merging andImproved Importance Diffusion
Author NameAffiliation
Danfeng Zhao College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Bo Wang College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Abstract:
A simple and effective content-aware image resizing method is proposed based on the row/column merging and improved importance diffusion, which preserves the important regions in an image as well as the global visual effect. By repeatedly merging two rows/columns into one row/column or inserting a new row/column between two rows/columns, this method realizes image-resolution reduction and expansion. The importance of the merged row/column is promoted and diffused to four rows/columns around the merged one, which is to avoid the unwanted image distortions resulted from excessively merging of un-important regions. In addition, the proposed method introduces the direction of gradient vector in the low-pass filter to reduce the interference caused by complex texture background and protect important content better. Furthermore, according to human mechanics principles, different weights are given to the row and column direction components of gradient vectors which can obtain better global visual effect. Experimented results show that the proposed method satisfied in not only visual effect but also objective evaluation.
Key words:  content-aware image resizing  merging  importance diffusion  gradient vector
DOI:10.11916/j.issn.1005-9113.2015.02.010
Clc Number:TN911.73
Fund:

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