Closed-form least-squares technique for adaptive linear image interpolation

An adaptive linear image interpolation method based on the least-squares technique is proposed. A generic adaptive interpolation framework is introduced to provide a simple closed-form formula for adaptive image interpolation. Experimental results indicate that the proposed interpolation method outperforms existing methods in terms of objective and subjective image quality.

[1]  Michael Unser,et al.  Splines: a perfect fit for signal and image processing , 1999, IEEE Signal Process. Mag..

[2]  Jong-Ki Han,et al.  Parametric cubic convolution scaler for enlargement and reduction of image , 2000, IEEE Trans. Consumer Electron..

[3]  Thierry Blu,et al.  Linear interpolation revitalized , 2004, IEEE Transactions on Image Processing.

[4]  Hwang Soo Lee,et al.  Adaptive image interpolation based on local gradient features , 2004, IEEE Signal Process. Lett..

[5]  R. Keys Cubic convolution interpolation for digital image processing , 1981 .

[6]  Thierry Blu,et al.  MOMS: maximal-order interpolation of minimal support , 2001, IEEE Trans. Image Process..

[7]  Giovanni Ramponi,et al.  Warped distance for space-variant linear image interpolation , 1999, IEEE Trans. Image Process..