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Proceedings ArticleDOI

Canny edge based image expansion

Hongjian Shi, +1 more
- Vol. 1, pp 785-788
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TLDR
A Canny edge-based image expansion method that outperforms the pixel replication, the bilinear interpolation and the bicubic interpolation methods and gives crisp and less zigzag pictures.
Abstract
In this paper, a Canny edge-based image expansion method is introduced. Our proposed expansion method outperforms the pixel replication, the bilinear interpolation and the bicubic interpolation methods. It gives crisp and less zigzag pictures. Our method is applied on the image after it has been expanded using bilinear or bicubic interpolation. The edges of such an expanded image are obtained using the Canny edge detector. The values of pixels around the edges are modified to yield a crisper and less zigzagged picture.

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Citations
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Efficient edge detection in digital images using a cellular neural network optimized by differential evolution algorithm

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References
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Journal ArticleDOI

A Computational Approach to Edge Detection

TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI

New edge-directed interpolation

TL;DR: Simulation results demonstrate that the new interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional linear interpolation.
Journal ArticleDOI

Comparison of Interpolating Methods for Image Resampling

TL;DR: In this paper, the authors compared the performance of linear and cubic B-spline interpolation, linear interpolation and high-resolution cubic spline with edge enhancement with respect to the initial coordinate system.
Journal ArticleDOI

Subpixel edge localization and the interpolation of still images

TL;DR: The algorithm is based on a source model emphasizing the visual integrity of detected edges and incorporates a novel edge fitting operator that has been developed for this application, and produces an image of increased resolution with noticeably sharper edges and lower mean-squared reconstruction error than that produced by linear techniques.
Proceedings ArticleDOI

Edge-directed interpolation

TL;DR: A new method for digitally interpolating images to higher resolution based on bilinear interpolation modified to prevent interpolation across edges, as determined from the estimated high resolution edge map is presented.
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