An Innovative Approach to Performing Color Correction and Equalization for Creating Mars Global Color Image Mosaics Using Tianwen-1 MoRIC Images

Mars is rich in color information, and color images can more vividly represent its surface morphology, which helps scientists accurately interpret the geomorphological and geological characteristics of Mars. However, modern telescopes and remote sensing technology still haven't provided a quantitative answer to the exact colors of the Martian surface. The Moderate Resolution Imaging Camera (MoRIC) on Tianwen-1 is a "true color" camera with red, green, and blue spectral bands matching the spectral response range of human eyes. In around 8.3 months, it obtained color images covering the entire globe of Mars. But affected by illumination and atmospheric conditions, there are conspicuous stripes along the image strip direction in the color mosaic map, and the overall tone is noticeably red. Color difference analysis reveals that in the high latitudes of the northern hemisphere, the color differences mainly stem from varying atmospheric conditions during mapping; in the middle and low latitudes, they're mainly due to different lighting conditions; while in the high latitudes of the southern hemisphere, the color differences (measured by CIEDE2000, ΔE00) are mainly caused by the changes in surface features resulting from the seasonal melting of the ice caps. In this work, we proposed a novel approach to quantified color correction and equalization for generating Mars global color image mosaics from the MoRIC images. This approach makes the image brightness and tone visually consistent under different imaging conditions and maintains global consistency in the tones of the same surface features. A significant portion (80.1%) of the overlapped regions has color differences concentrated within ΔE00≤3.0, which greatly improves the issue of color and brightness inconsistencies in the original images (Level 2C). After processing, the tone of the global color mosaic map shows the "terracotta hue" that we expect for Mars images and is a good approximation of what the human eye would see.