基于定量的人工智能图像提取技术的唐三财人像图像重建

Shengwei Qiu
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引用次数: 0

摘要

:在研究唐三才人像的过程中,由于光学系统、运动、大气湍流等原因,有些图像会出现退化,因此需要对图像进行恢复。采用最佳的恢复方法,恢复的图像可以满足要求。实际上,图像恢复的目的是对退化后的图像进行处理,使恢复后的图像更接近原始图像。本文以唐三才人像为实验对象,对经典图像重建方法进行对比实验。结果表明,在本文选取的实验方法中,最小二乘法的图像重建质量最好,重建图像A的SSIM和PSNR指标值分别为0.9612和31.7612;在GAN、GA-GAN和Dense-GAN模型的性能比较中,基于GA-GAN模型的图像重建算法具有最好的性能。在实验使用的10张唐三才人像图像中,SIMM值最高为0.99,PSNR值最高为27.9345。
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Image Reconstruction of Tang Sancai Figurines Based on Artificial Intelligence Image Extraction Technology Based on Ration
: In the process of studying the Tang Sancai figurines, some images will be degraded due to optical system, motion, atmospheric turbulence, etc., so the images need to be restored. With the best restoration method, the restored image can meet the requirements. In fact, the purpose of image restoration is to process the degraded image to make the restored image closer to the original image. This paper conducts a comparative experiment on the classical image reconstruction methods, taking the images of Tang Sancai figurines as the experimental objects. The results show that the image reconstruction quality of the least squares method is the best among the methods selected for the experiment in this paper, and the SSIM and PSNR index values of the reconstructed image A are 0.9612 and 31.7612, respectively; in the performance comparison of GAN, GA-GAN, and Dense-GAN models, the image reconstruction algorithm based on the GA-GAN model has the best performance. Among the ten images of Tang Sancai figurines used in the experiment, the highest SIMM value is 0.99, and the highest PSNR value is 27.9345.
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CiteScore
1.40
自引率
16.70%
发文量
23
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