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

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)358-368
Number of pages11
JournalIET Image Processing
Volume9
Issue number5
DOIs
Publication statusPublished - 2015 May 1

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All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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