Enhancement of Anime Imaging Enlargement using Modified Super-Resolution CNN

Autor:	Intaniyom, Tanakit, Thananporn, Warinthorn, Woraratpanya, Kuntpong
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Anime is a storytelling medium similar to movies and books. Anime images are a kind of artworks, which are almost entirely drawn by hand. Hence, reproducing existing Anime with larger sizes and higher quality images is expensive. Therefore, we proposed a model based on convolutional neural networks to extract outstanding features of images, enlarge those images, and enhance the quality of Anime images. We trained the model with a training set of 160 images and a validation set of 20 images. We tested the trained model with a testing set of 20 images. The experimental results indicated that our model successfully enhanced the image quality with a larger image-size when compared with the common existing image enlargement and the original SRCNN method. Comment: 6 pages, 11 figures, to be published in The 11th Joint Symposium on Computational Intelligence (JSCI11)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2110.02321 Zobrazit plný text záznamu View this record from Arxiv