# A Color Matching Method for Mosaic HY-1 Satellite Images in Antarctica
## 1 Introduction
used Landsat data to conduct mosaic mapping of Antarctic images [10], and the blue-ice areas and their geographical distribution in Antarctica were mapped using the Landsat data associated with the snow grain-size image of the MODIS-Based Mosaic of Antarctica (MOA) dataset [11]. In addition, numerous studies have been conducted to map Antarctica using satellite imagery. [PERSON] et al. used Landsat data to study distribution maps of Adelie penguin colonies in Antarctica [12]. [PERSON] et al. [13] and [PERSON] et al. [14] used satellite thermal infrared mapping to discover the ultracold surface of East Antarctica, the coldest place on earth. [PERSON] et al. mapped the ice velocity in Antarctica from Landsat 8 images and InSAR, and revealed mass loss in Wilkes Land, East Antarctica [15]. Image mosaicking is a technique to seamlessly fuse multiple images with overlapping areas into a single composite image [2]. Image registration is an underlying requirement for a successful mosaic. On the one hand, for images without geographic reference information, the purpose of image registration and stitching can be achieved by finding the feature information on the image [16; 17], and then establishing a model based on the feature information [18]. On the other hand, for images with geographic reference information, \begin{table}
\begin{tabular}{l l} \hline \hline
**HY-1C/D** & \\ \hline Launch date & 7 September 2018 (HY-1C), 11 June 2020 (HY-1D) \\ \hline \multirow{3}{*}{Orbital} & Sun-synchronous orbit, altitude of 782 km, inclination = 98.6\({}^{\circ}\) \\  & HY-1C LTDN (local time on descending node) = 10:30 \(\pm\) 30 min \\  & HY-1D LTAN (local time on ascending node) = 13:30 \(\pm\) 30 min. \\ \hline \multirow{3}{*}{Instruments} & COCTS (China ocean color and temperature scanner) \\  & CZI (Coastal Zone Imager) \\ \cline{1-1}  & UVI (ultraviolet imager) \\ \cline{1-1}  & SCS (satellite calibration spectrometer) \\ \cline{1-1}  & AIS (automatic identification system) \\ \hline \multirow{2}{*}{Observation objective} & Global ocean-color, sea-surface temperature, sea-ice, dynamic \\ \cline{1-1}  & environment information of coastal zone \\ \hline \end{tabular}
\end{table} 
Table 1: HY-1C/D satellite introduction. image registration can be directly based on geographic information. In general, geographic registration is mostly used for satellite imagery. Satellite image mosaicking usually consists of five aspects: image registration, extraction of overlapping areas, radiometric normalization (also called radiometric balancing, color adjustment, or color consistency matching), seamline detection, and image blending [19]. Color consistency matching between different images is an important process during image mosaicking, and the main purpose of this process is to eliminate the color differences between mosaic images and make the color consistent. In this paper, we study the color consistency matching method using the HY-1C/D images from Antarctica. Generally, the image color consistency matching process includes single-image illumination homogenization processing and multi-image color consistency processing [20]. [PERSON] et al. used HY-1C data to study a color consistency processing method between images of Antarctica [21]. Image illumination homogenization processing is mainly used to solve the problem of uneven light inside the image, especially for remote sensing images with large swaths. Uneven light correction methods include illumination uniform methods based on additive models, such as the background fitting method and MASK method [22; 23], and multiplicative models for illumination uniform methods, such as the homomorphic filtering method [24] and retinex method [25; 26]. [PERSON] et al. [27] made a comparative analysis from the different illumination uniform experimental results to address image processing quality and algorithm execution efficiency. The results show that the MASK algorithm has the best illumination uniform effect.