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题名:
Study of gray image pseudo-color processing algorithms
作者: Hu, Jinlong1,2; Peng, Xianrong1; Xu, Zhiyong1
出版日期: 2012
会议名称: Proceedings of SPIE: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes
会议日期: 2012
DOI: 10.1117/12.977197
通讯作者: Hu, J.
中文摘要: In gray images which contain abundant information, if the differences between adjacent pixels' intensity are small, the required information can not be extracted by humans, since humans are more sensitive to color images than gray images. If gray images are transformed to pseudo-color images, the details of images will be more explicit, and the target will be recognized more easily. There are two methods (in frequency field and in spatial field) to realize pseudo-color enhancement of gray images. The first method is mainly the filtering in frequency field, and the second is the equal density pseudo-color coding methods which mainly include density segmentation coding, function transformation and complementary pseudo-color coding. Moreover, there are many other methods to realize pseudo-color enhancement, such as pixel's self-transformation based on RGB tri-primary, pseudo-color coding from phase-modulated image based on RGB color model, pseudo-color coding of high gray-resolution image, et al. However, above methods are tailored to a particular situation and transformations are based on RGB color space. In order to improve the visual effect, the method based on RGB color space and pixels' self-transformation is improved in this paper, which is based on HIS color space. Compared with other methods, some gray images with ordinary formats can be processed, and many gray images can be transformed to pseudo-color images with 24 bits. The experiment shows that the processed image has abundant levels, which is consistent with human's perception. © 2012 SPIE.
英文摘要: In gray images which contain abundant information, if the differences between adjacent pixels' intensity are small, the required information can not be extracted by humans, since humans are more sensitive to color images than gray images. If gray images are transformed to pseudo-color images, the details of images will be more explicit, and the target will be recognized more easily. There are two methods (in frequency field and in spatial field) to realize pseudo-color enhancement of gray images. The first method is mainly the filtering in frequency field, and the second is the equal density pseudo-color coding methods which mainly include density segmentation coding, function transformation and complementary pseudo-color coding. Moreover, there are many other methods to realize pseudo-color enhancement, such as pixel's self-transformation based on RGB tri-primary, pseudo-color coding from phase-modulated image based on RGB color model, pseudo-color coding of high gray-resolution image, et al. However, above methods are tailored to a particular situation and transformations are based on RGB color space. In order to improve the visual effect, the method based on RGB color space and pixels' self-transformation is improved in this paper, which is based on HIS color space. Compared with other methods, some gray images with ordinary formats can be processed, and many gray images can be transformed to pseudo-color images with 24 bits. The experiment shows that the processed image has abundant levels, which is consistent with human's perception. © 2012 SPIE.
收录类别: Ei
语种: 英语
卷号: 8415
ISSN号: 0277786X
文章类型: 会议论文
页码: 841519
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7689
Appears in Collections:光电探测与信号处理研究室(五室)_会议论文

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作者单位: 1. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan, 610209, China
2. Graduate School, Chinese Academy of Sciences, Beijing, 100039, China

Recommended Citation:
Hu, Jinlong,Peng, Xianrong,Xu, Zhiyong. Study of gray image pseudo-color processing algorithms[C]. 见:Proceedings of SPIE: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes. 2012.
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