Comparison of Histogram Matching Preprocessing Methods for Generating Natural GOCI-II Full Disk Images Kim, S., Song, S. and Rhee, S.*
3D Labs Co., Ltd. Incheon, Republic of Korea
*ahmkun[at]3dlabs.co.kr
Abstract
Full disk imagery is significant in that it enables observation of atmospheric and oceanic changes on a global scale. It is particularly important for time-series analysis, which supports various applications such as cloud tracking and ocean current monitoring through continuous image acquisition. Accordingly, satellites such as the GOES series (USA), Himawari series (Japan), and Meteosat series (EU) continuously provide full disk imagery and derived products. Korea also contributes with its GEO-KOMPSAT-2A and 2B satellites, which provide global coverage for atmospheric and oceanic monitoring. Similar to conventional full disk systems, the GOCI-II payload aboard the GK-2B satellite captures slot-by-slot images that must be mosaicked into a single full disk image. However, this sequential acquisition introduces time differences between slots, resulting in pixel value imbalances that can degrade analytical accuracy. In addition, brightness range inconsistencies between slots can lead to visually unnatural mosaicked images. In this paper, we aimed to generate visually natural full disk images by using histogram matching in the image matching process. In this process, we performed preprocessing procedures such as changing the matching order, removing cloud regions, and stretching the image, and compared the results. Experimental results showed that the most visually natural full disk images were produced by adjusting the histogram offsets of cloud-unfiltered input images to the reference image and performing matching in slot number order. These results indicate potential for use as baseline data in global monitoring systems and time-series pattern analysis. However, since histogram matching directly modifies pixel values, further validation is necessary to ensure the reliability of time-series analyses based on these processed images.
Keywords: GOCI-II, Full disk mosaicking, Histogram matching, Ocean satellite, Image processing
Topic: Topic C: Emerging Technologies in Remote Sensing
