An image zooming technique based on vector quantization approximation

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摘要

An image zooming method based on vector quantization approximation for magnifying gray-scale and color image by a factor of 2 is proposed. In our proposed method, the unknown pixel values on the image are interpolated by using a vector quantization codebook based on their local information. In comparison of our method with the locally adaptive zooming algorithm published in [S. Battiato, G. Gallo, F. Stanco, A locally adaptive zooming algorithm for digital images, Image and Vision Computing, 20(11) (2002) 805–812.], our experimental results have demonstrated that the image quality of the enlarged image is superior to the method in [S. Battiato, G. Gallo, F. Stanco, A locally adaptive zooming algorithm for digital images, Image and Vision Computing, 20(11) (2002) 805–812.]. Not only is our method simpler to implement by utilizing a table look-up technique on codebook, but also is much easier in translating to color images than that of [S. Battiato, G. Gallo, F. Stanco, A locally adaptive zooming algorithm for digital images, Image and Vision Computing, 20(11) (2002) 805–812.] by replacing an adequate codebook.

论文关键词:Image zooming,Image magnification,Vector quantization

论文评审过程:Received 29 January 2004, Revised 21 July 2005, Accepted 26 July 2005, Available online 29 September 2005.

论文官网地址:https://doi.org/10.1016/j.imavis.2005.07.020