Poster + Paper
27 November 2023 Color fusion method with a combination of steerable pyramid color transfer and ICA
Author Affiliations +
Conference Poster
Abstract
Independent Component Analysis (ICA) applied to the image processing is the analysis of the characteristics of the human visual system based on sparse code. ICA provides a novel transfer domain method along multiple directions and offers excellent characteristic expression and an edge modeling feature. Color transfer is currently the best way to obtain natural colorization for grayscale image. By combining these two methods, our study focused on the exploration of an approach to natural color fusion by highlighting the corresponding band characteristics. A training image database was established and the characteristics of independent band were extracted to construct an analysis kernel and a synthesis kernel of the ICA domain. In the ICA domain, we applied regional energy fusion rule to generate a grayscale fusion image. According to the visual task, the source image was linearly projected to the color channels in brightness-color separation color space, giving color information to the grayscale fused image. Using a steerable pyramid, the sub-band image of source color image and the reference color image were generated and transferred with the mean and variance independently. Finally, a fused image with a daytime color appearance was obtained. The perception of the human eye and the objective evaluation indicated that the fused image highlights the band characteristics and enhances details with natural and visually pleasing colors, which further improves scene perception.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yuan Luo and Pingping Yun "Color fusion method with a combination of steerable pyramid color transfer and ICA", Proc. SPIE 12766, Advanced Optical Imaging Technologies VI, 1276616 (27 November 2023); https://doi.org/10.1117/12.2680899
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KEYWORDS
Image fusion

Color

Image enhancement

Independent component analysis

Eye

Mid infrared

Image quality

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