The Moon Mineralogy Mapper(M3) Data Preprocessing Method Research And Application

Moon as the only satellite of the earth is formed in around 4.5 billion years,which in the same period with the earth. Since space technology has not developed to routinization, mineral composition, distribution of gravity, magnetic field data and other information on the moon is still mainly rely on satellite remote sensing. Moon Mineralogy Mapper(referred to as the M3) as the one of the hyperspectral imaging sensor for moon which developed by NASA, its mainly role is identify the moon’s mineral characteristics in the visible and near infrared(0.42-3.0 m) range. And the use of the data has important significance in the study of the geological structure of the moon.This article is based on the " Study on Application of remote sensing data of extraterrestrial key areas " project, conducted studies on M3 data preprocessing method, image denoising and a series of data processing on the basis of the performance parameters of the M3 sensor, the basic method of image data acquisition and other aspects of the data characteristics are analyzed. And analysis the mineral information extraction methods of M3 data by taking Aristarchus as the research area, olivine composition as an example. At the same time, the accuracy of the method is verified. The main contents include:(1)In order to eliminate the influence of the light intensity irregular variation caused by the geometric observation condition of the planet surface. In this paper, we use the improved Lommel-Seeliger photometric correction model, combined with method of phase function fitting methods to achieve spectral reconstruction of the image in the study area. And verify the accuracy for image after phase function fitting of the correlation coefficient calculation methods. The results showed that in addition to the negative value of correlation coefficient represents the irregular change of image radiance, caused by the noise of band 1 and 2, the correlation coefficients of the other bands are all above 0.9, which means the accuracy of the fitting result is proved.(2)Using Savitzky-Golay method, which eliminates the spectral domain noise generated by M3 data for image imaging because of the image forming time, the terrain factor, the mixed pixel and so on, further increased by accuracy of image interpretation.(3)On the basis of the determination of Modified Gauss model(MGM) fitting algorithm and the technical process of extracting mineral information, the use of MGM fitting methods to complete the olivine composition of Aristarchus extraction. Compared with the existing research results, it is proved that the results have high accuracy.