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

机译:一种具有新颖评估方法的快速大规模图像放大方法:基于基准函数的峰值信噪比

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摘要

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.
机译:在这项研究中,提出了一种客观的新颖评估方法,该方法通过基于基准函数的峰值信噪比实现,特别适合评估小尺寸图像的大规模放大的性能。此外,提出了一种通过改进的离散余弦变换(DCT)的快速大规模图像放大方法,以提高图像缩放的质量和速度。提出的基于DCT的图像放大算法通过将DCT矩阵相乘节省了计算时间。与传统的DCT方法相比,改进的方法克服了图像偏移和块效应。与其他插值方法相比,DCT放大在边缘细节方面优于它们,因为它考虑了整个图像的全局频率信息。随着DCT的扩大,通过采用不同大小的变换矩阵,可以轻松实现基于像素大小的任意缩放。说明性示例说明了该方法的有效性。

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