Fast large-scale image enlargement method with a novel evaluation approach: benchmark function-based peak signal-to-noise ratio

Shu-Mei Guo; Chih-Yuan Hsu; Gia-Hao Kuo; Jason Sheng-Hong Tsai

Fast large-scale image enlargement method with a novel evaluation approach: benchmark function-based peak signal-to-noise ratio

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Author(s): Shu-Mei Guo ¹ ; Chih-Yuan Hsu ¹ ; Gia-Hao Kuo ¹ ; Jason Sheng-Hong Tsai ²
- Affiliations: 1: Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan 701, Taiwan;
  2: Control System Laboratory, Department of Electrical Engineering, National Cheng-Kung University, Tainan 701, Taiwan
Source: Volume 9, Issue 5, May 2015, p. 358 – 368
DOI: 10.1049/iet-ipr.2014.0293 , Print ISSN 1751-9659, Online ISSN 1751-9667

Received 06/08/2013, Accepted 13/09/2014, Revised 03/09/2014, Published 15/10/2014

An objective novel evaluation approach, implemented by the benchmark function-based peak signal-to-noise ratio, particularly suitable for evaluating the performance of a large-scale enlargement of a small size image is proposed in this study. Also, a fast large-scale image enlargement method via the improved discrete cosine transform (DCT) is proposed to improve the quality and speed of image zooming. The proposed image enlargement algorithm based on DCT saves computation time by multiplication of the DCT matrix. Compared with the traditional DCT approach, the improved approach overcomes the image shifting and blocky effects. In comparisons with other interpolation methods, DCT enlargement outperforms them in edge details because it considers the global frequency information of the whole image. With the DCT enlargement, it is easy to implement the arbitrary pixel-size-based zooming of an image by employing the different size of transform matrix. Illustrative examples show the effectiveness of the proposed approach.

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Fast large-scale image enlargement method with a novel evaluation approach: benchmark function-based peak signal-to-noise ratio

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