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

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.

Inspec keywords: discrete cosine transforms; interpolation; matrix algebra; image processing; edge detection

Other keywords: interpolation methods; global frequency information; small size image; matrix transform; fast large scale image enlargement method; discrete cosine transform; image enlargement algorithm; peak signal-to-noise ratio; DCT matrix; benchmark function; image zooming; edge details; novel evaluation approach

Subjects: Interpolation and function approximation (numerical analysis); Computer vision and image processing techniques; Linear algebra (numerical analysis); Optical, image and video signal processing; Linear algebra (numerical analysis); Interpolation and function approximation (numerical analysis); Integral transforms in numerical analysis; Integral transforms in numerical analysis

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