Cavanagh, Patrick D.Li, Lin2015-11-182015-11-182012-04-13Patrick D. Cavanagh and Lin Li. (2012, April 13). BAND SELECTION METHOD APPLIED TO M3 (MOON MINERALOGY MAPPER). Poster session presented at IUPUI Research Day 2012, Indianapolis, Indiana.https://hdl.handle.net/1805/7475poster abstractRemote sensing optical sensors, such as those on board satellites and planetary probes, are able to detect and measure solar radiation at both im-proved spectral and spatial resolution. In particular, a hyperspectral dataset often consists of tens to hundreds of specified wavelength bands and con-tains a vast amount of spectral information for potential processing. One drawback of such a large spectral dataset is information redundancy result-ing from high correlation between narrow spectral bands. Reducing the data dimensionality is critical in practical hyperspectral remote sensing applica-tions. Price’s method is a band selection approach that uses a small subset of bands to accurately reconstruct the full hyperspectral dataset. The method seeks to represent the dataset by a weighted sum of basis functions. An it-erative process is used to successively approximate the full dataset. The process ends when the last basis function no longer provides a significant contribution to the reconstruction of the dataset, i.e. the basis function is dominated by noise. The research presented examines the feasibility of Price’s method for ex-tracting an optimal band subset from recently acquired lunar hyperspectral images recorded by the Moon Mineralogy Mapper (M3) instrument on board the Chandrayaan-1 spacecraft. The Apollo 17 landing site was used for test-ing of the band selection method. Preliminary results indicate that the band selection method is able to successfully reconstruct the original hyperspectral dataset with minimal error. In a recent test case, 15 bands were used to reconstruct the original 74 bands of reflectance data. This represents an accurate reconstruction using only 20% of the original dataset. The results from this study can help to configure spectral channels of fu-ture optical instruments for lunar exploration. The channels can be chosen based on the knowledge of which wavelength bands represent the greatest relevant information for characterizing geology of a particular location.en-USM3 (MOON MINERALOGY MAPPER)remote sensingwavelength bandsspectral datasetPoster