An objective comparison of 3-D image interpolation methods

1998 ◽  
Vol 17 (4) ◽  
pp. 642-652 ◽  
Author(s):  
G.J. Grevera ◽  
J.K. Udupa
Keyword(s):  
Image Interpolation ◽  
Interpolation Methods

A survey on image interpolation methods

2010 ◽  
Author(s):  
Vinit Jakhetiya ◽  
Ashok Kumar ◽  
Anil Kumar Tiwari
Keyword(s):  
Image Interpolation ◽  
Interpolation Methods

Image Interpolation Algorithm Based on Edge Features

2011 ◽  
Vol 50-51 ◽  
pp. 564-567
Author(s):  
Yun Feng Yang ◽  
Xiao Guang Wei ◽  
Zhi Xun Su
Keyword(s):  
Interpolation Method ◽  
Spline Interpolation ◽  
Weighted Average ◽  
Image Interpolation ◽  
Interpolation Process ◽  
Edge Information ◽  
B Spline ◽  
Interpolation Methods ◽  
Distance Weighted ◽  
Edge Features

Image interpolation is used widely in the computer vision. Holding edge information is main problem in the image interpolation. By using bilinear and bicubic B-spline interpolation methods, a novel image interpolation approach was proposed in this paper. Firstly, inverse distance weighted average method was used to reduce image’s noise. Secondly, edge detection operator was used to extract image's edges information. It can help us to select different interpolation methods in the image interpolation process. Finally, we selected bilinear interpolation approach at non-edge regions, and bicubic B-spline interpolation method was used near edges regions. Further more, control vertexes were computed from pixels with calculation formula which has been simplified in the B-spline interpolation process. Experiments showed the interpolated image by the proposed method had good vision results for it could hold image's edge information effectively.

Medical Image Interpolation Algorithm Based on the Organization of Correlation

2014 ◽  
Vol 513-517 ◽  
pp. 3744-3749
Author(s):  
Yue Zhou ◽  
Jia Xin Chen
Keyword(s):  
Computational Complexity ◽  
3D Reconstruction ◽  
Medical Image ◽  
Image Interpolation ◽  
Interpolation Algorithm ◽  
Lower Efficiency ◽  
Interpolation Methods

According to the problem such as blurred border of images and lower efficiency caused by present interpolation methods, an interslice interpolation based on the relativity for medical image is presented in this paper. This algorithm makes good use of voxel relativity and structure relativity and then the different methods are adopted to interpolate the different points, In addition, error checkout is introduced to check the mismatching points.The experiments show that the proposed algorithm has less computational complexity and improves the quality of image, at the same time, the result can be used to 3D reconstruction effectively.

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