Image interpolation based on Hessian analysis
Sangho Yoon, Young Hwan Kim · 2016
This paper proposes a novel interpolation method using edge orientation vector calculated by Hessian matrix. Existing polynomial-based interpolation methods cause blurring effects on edge. In addition, existing edge-based interpolation methods are suffered from edge aliasing and color distortion. To compensate for these problems, we propose an improved edge-based interpolation method considering edge direction on neighbor pixels. To interpolate image, unknown pixels are interpolated by internal division. To determine internal division ratio, the proposed method calculates the edge orientations for diagonal pixels and norm of pixel value differences for horizontal and vertical pixels. The proposed method improves the quality of interpolated images by increasing the average peak signal-to-ratio by 3.33 dB compared to benchmark method.