This paper proposes an edge-directed interpolation algorithm for natural images. The basic idea is to first estimate local covariance coefficients a low-resolution image and then use these covariance estimates to adapt the interpolation at a higher resolution based on the geometric duality between the low-resolution covariance and the high-resolution covariance. The edge-directed property of covariance-based adaptation attributes to its capability of tuning the interpolation coefficients to match an arbitrarily oriented step edge. A hybrid approach of switching between bilinear interpolation and covariance-based adaptive interpolation is proposed to reduce the overall computational complexity. Two important applications of the new interpolation algorithm are studied: resolution enhancement of grayscale images and reconstruction of color images CCD samples. Simulation results demonstrate that our new interpolation algorithm substantially improves the subjective quality

New edge directed interpolationNEDI.pdf

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