The basic principle of the patch-matching based style transfer is to substitute the patches of the content image feature maps by the closest patches from the style image feature maps. Since the finite features harvested from one single aesthetic style image are inadequate to represent the rich textures of the content natural image, existing techniques treat the full-channel style feature patches as simple signal tensors and create new style feature patches via signal-level fusion, which ignore the implicit diversities existed in style features and thus fail for generating better stylised results. In this paper, we propose a Retinex theory guided, channel-grouping based patch swap technique to solve the above challenges. Channel-grouping strategy groups the style feature maps into surface and texture channels, which prevents the winner-takes-all problem. Retinex theory based decomposition controls a more stable channel code rate generation. In addition, we provide complementary fusion and multi-scale generation strategy to prevent unexpected black area and over-stylised results respectively. Experimental results demonstrate that the proposed method outperforms the existing techniques in providing more style-consistent textures while keeping the content fidelity.

翻译：基于补丁匹配的风格迁移的基本原理是，用风格图像特征图中最相似的补丁替换内容图像特征图的补丁。由于从单张美学风格图像中提取的有限特征不足以表现内容自然图像的丰富纹理，现有技术将全通道风格特征补丁视为简单信号张量，并通过信号级融合生成新的风格特征补丁，这忽视了风格特征中隐含的多样性，因此难以生成更优的风格化结果。本文提出一种基于Retinex理论引导的通道分组补丁交换技术来解决上述挑战。通道分组策略将风格特征图分为表面通道和纹理通道，从而避免了"赢家通吃"问题。基于Retinex理论的分解方法能更稳定地控制通道编码率生成。此外，我们分别提供了互补融合和多尺度生成策略，以避免意外的黑色区域和过度风格化问题。实验结果表明，所提方法在保持内容保真度的同时，能生成更具风格一致性的纹理，优于现有技术。