{"title":"Color transfer method based on saliency features for color images","authors":"Shi Bao, Ye Zhao, Yatu Ji, Nier Wu, Gao Le","doi":"10.1007/s10043-024-00888-2","DOIUrl":null,"url":null,"abstract":"<p>With growing demands for higher image quality in the fields of film, video post-production, image restoration, art creation, and computer vision, color transfer between images has become an important research area. Based on previous research on color transfer techniques, this paper proposes a color transfer method for images based on saliency features, aiming at automatic color migration between them. Transferring colors based on the saliency features of the input image can avoid the problem of unnatural color of the output image due to mixing of colors from different regions. First, the local variances of both the original and reference images are calculated, serving as a temporary saliency feature map. This is followed by obtaining a refined saliency feature map after undergoing processes such as minimization filtering, binarization, expansion, and iteration. Subsequently, color is transferred between the saliency and non-saliency regions of the original and reference images. To avoid the generation of pseudo-contours, the image is then refined using base projection. Finally, an output image is obtained by fusing the base-projected image with the outcome from Reinhard’s method, ensuring the output retains its naturalness and consistency. We conducted experiments with different types of images such as natural landscapes, buildings, and art paintings. The experimental results show that the method proposed in this paper not only retains the intricacies of the original image but also offers fuller and more realistic color renditions.</p>","PeriodicalId":722,"journal":{"name":"Optical Review","volume":"38 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Review","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1007/s10043-024-00888-2","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
With growing demands for higher image quality in the fields of film, video post-production, image restoration, art creation, and computer vision, color transfer between images has become an important research area. Based on previous research on color transfer techniques, this paper proposes a color transfer method for images based on saliency features, aiming at automatic color migration between them. Transferring colors based on the saliency features of the input image can avoid the problem of unnatural color of the output image due to mixing of colors from different regions. First, the local variances of both the original and reference images are calculated, serving as a temporary saliency feature map. This is followed by obtaining a refined saliency feature map after undergoing processes such as minimization filtering, binarization, expansion, and iteration. Subsequently, color is transferred between the saliency and non-saliency regions of the original and reference images. To avoid the generation of pseudo-contours, the image is then refined using base projection. Finally, an output image is obtained by fusing the base-projected image with the outcome from Reinhard’s method, ensuring the output retains its naturalness and consistency. We conducted experiments with different types of images such as natural landscapes, buildings, and art paintings. The experimental results show that the method proposed in this paper not only retains the intricacies of the original image but also offers fuller and more realistic color renditions.
期刊介绍:
Optical Review is an international journal published by the Optical Society of Japan. The scope of the journal is:
General and physical optics;
Quantum optics and spectroscopy;
Information optics;
Photonics and optoelectronics;
Biomedical photonics and biological optics;
Lasers;
Nonlinear optics;
Optical systems and technologies;
Optical materials and manufacturing technologies;
Vision;
Infrared and short wavelength optics;
Cross-disciplinary areas such as environmental, energy, food, agriculture and space technologies;
Other optical methods and applications.