电子科技2025，Vol.38Issue(6)：65-73,9.DOI:10.16180/j.cnki.issn1007-7820.2025.06.010
基于CBAM残差块结合纹理采样器的水墨迁移算法
Ink Transfer Algorithm Based on CBAM Residual Block Combined with Texture Sampler
摘要
Abstract
In view of the problems of ink style transfer algorithm,such as unclear lines,chaotic textures and poor color reconstruction,a new lightweight ink style transfer neural network IWSGAN(Ink and Wash Style Genera-tive Adversarial Networks)is proposed in this study.The CBAM(Convolutional Block Attention Module)residual block is used to calculate the channel spatial attention of the feature map,which improves the algorithm's adoption rate of effective information.In combination with the ink texture salience sampler ITSS(Ink-Texture-Saliency-Sam-pler),the local image blocks of ink painting salience are sampled from the training data to make the line texture of the transferred ink picture more ink texture.Five different loss functions are used to constrain the high-level seman-tics of the content image and the generated image to facilitate consistency in style characteristics.The experimental results show that the image generated by IWSGAN retains more content features,the texture details of the lines are more vivid,the color reconstruction performance is excellent,and the image quality is significantly improved.关键词
风格迁移/生成对抗网络/CBAM残差块/注意力机制/ITSS/局部对抗/水墨迁移/消融实验Key words
style transfer/generative adversarial network/CBAM residual block/attention mechanism/ITSS/lo-cal adversarial/ink transfer/ablation experiment分类
计算机与自动化引用本文复制引用
刘雪莉,杜洪波,袁雪丰,朱立军..基于CBAM残差块结合纹理采样器的水墨迁移算法[J].电子科技,2025,38(6):65-73,9.基金项目
国家自然科学基金(11861003) （11861003）
辽宁省教育厅高等学校基本科研项目(LJKZ0157)National Natural Science Foundation of China(11861003) （LJKZ0157）
Basic Scientific Research Project of Higher Education Department of Liaoning(LJKZ0157) （LJKZ0157）
