多媒体数据特征提取技术在民间艺术创作中的应用

Ying-ying Gong
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引用次数: 0

摘要

在智能化背景下,为了更便捷地进行民间美术创作,本文将多媒体数据特征新技术融入到民间美术创作中,实现民间美术的可持续发展。具体来说,本文基于小波变换的方法,将民间美术图像分解为不同尺度、不同分辨率的图像,从而获得更加清晰的作品,有利于民间美术的创作与传播。以峰值信噪比(PSNR)为评价标准,用五幅经典民间艺术图像检验图像增强的效果。实验结果表明,经过数据特征提取后,民间艺术作品的 PSNR 均高于 30,达到了数据特征提取的要求。进一步表明,多媒体数字特征技术在民间美术作品中具有良好的应用效果,有利于民间美术的传承与创作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Multimedia Data Feature Extraction Technology in Folk Art Creation
In the intelligent background, in order to carry out the folk art creation more conveniently, this article integrates the new technology of multimedia data features into the folk art creation to achieve the sustainable development of folk art. Specifically, based on the method of wavelet transform, this article decomposes folk art images into images of different scales and different resolutions to obtain clearer works, which is beneficial to the creation and dissemination of folk art. With the peak signal to noise ratio (PSNR) as the evaluation criterion, five classical folk art images are used to test the effect of image enhancement. The experimental results show that the PSNR of the folk art works after data feature extraction is higher than 30, which meets the requirements of data feature extraction. It further shows that multimedia digital feature technology has a good application effect on folk art works, which is conducive to the inheritance and creation of folk art.
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