To resolve the problem that more distortions occured in image retargeting algorithm, an image retargeting algorithm based on the Parallel Translation of Gridlines (PTG) was put forward. Firstly, Achanta algorithm was used to compute the important degree and extract the main object. Secondly, the optimal grid line displacement was calculated. Using grid lines movement can keep the size of important areas and protect the aspect ratio of object and the dual constraints can avoid distortion. At the same time, the lower and upper thresholds were used to restrain the distortion caused by excessively narrowing and widening grids. Finally, in order to achieve better effect, a edge discarding process was introduced to assign wider space to the important area for reducing the distortion. Image retargeting survey system was used to compare PTG with the methods including column removal method with importance diffusion, seam carving method with importance diffusion and grid warping method, and PTG got a better result in images with obvious main goal. The experimental results show that PTG not only has less distortion but also retains the interest area and important object of the image than the comparison methods.
[1] VAQUERO D, TURK M, PULLI K, et al. A survey of image retargeting techniques [C]//ADIP 2010: Proceedings of the 2010 Applications of Digital Image Processing XXXIII, SPIE 7798. Bellingham: SPIE, 2010: 1-9. [2] AVIDAN S, SHAMIR A. Seam carving for content-aware image resizing [J]. ACM Transactions on Graphics, 2007,26(3): Article No. 10. [3] RUBINSTEIN M, SHAMIR A, AVIDAN S. Improved seam carving for video retargeting [J]. ACM Transactions on Graphics, 2008, 27(3): Article No. 16. [4] RUBINSTEIN M, SHAMIR A, AVIDAN S. Multi-operator media retargeting [J]. ACM Transactions on Graphics, 2009, 28(3): Article No. 23. [5] CHO S, CHOI H, MATSUSHITA Y, et al. Image retargeting using importance diffusion[C]//ICIP 2009: Proceedings of the 2009 16th IEEE International Conference on Image Processing. Piscataway: IEEE, 2009: 977-980. [6] BASHA T, MOSES Y, AVIDAN S. Geometrically consistent stereo seam carving [C]//ICCV 2011: Proceedings of the 2011 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2011: 1816-1823. [7] CHOI K-S, NAM H-M, BYUN K-Y, et al. Content-aware 3D image retargeting for mobile devices [C]//ICCE 2011: Proceedings of the 2011 IEEE Conference on Consumer Electronics. Piscataway: IEEE, 2011:647-648. [8] WANG Y-S, TAI C-L, SORKINE O, et al. Optimized scale-and-stretch for image resizing [J]. ACM Transactions on Graphics, 2008, 27(5): Article No. 118. [9] GAL R, SORKINE O, COHEN-OR D. Feature-aware texturing [C]//EGSR 2006: Proceedings of the 17th Eurographics Conference on Rendering. Aire-la-Ville: Eurographics Association, 2006: 297-303. [10] WOLF L, GUTTMANN M, COHEN-OR D. Non-homogeneous content-driven video-retargeting [C]//ICCV 2007: Proceedings of the 2007 11th IEEE International Conference on Computer Vision. Piscataway: IEEE, 2007: 301-310. [11] ITTI L, KOCH C, NIEBUR E. A model of saliency-based visual attention for rapid scene analysis [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259. [12] FLETCHER R. Practical methods of optimization [M]. Hoboken: John Wiley and Sons, 1990. [13] WEI J-D, LIN Y-J, WU Y-J. A patch analysis method to detect seam carved images [J]. Pattern Recognition Letters, 2014, 36: 100-106. [14] WANG B, XIONG H, REN Z, et al. Deformable shape preserving video retargeting with salient curve matching [J]. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2014, 4(1): 82-94. [15] ACHANTA R, HEMAMI S, ESTRADA F, et al. Frequency-tuned salient region detection [C]//CVPR 2009: Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2009: 1597-1604. [16] RUBINSTEIN M, GUTIERREZ D, SORKINE O, et al. A comparative study of image retargeting[J]. ACM Transactions on Graphics, 2010, 29(6): Article No. 160.
2015, Vol. 35 
