Spatial Spectral Band Selection for Enhanced Hyperspectral Remote Sensing Classification Applications.

Despite the numerous band selection (BS) algorithms reported in the field, most if not all have exhibited maximal accuracy when more spectral bands are utilized for classification. This apparently disagrees with the theoretical model of the 'curse of dimensionality' phenomenon, without apparent explanations. If it were true, then BS would be deemed as an academic piece of research without real benefits to practical applications. This paper presents a spatial spectral mutual information (SSMI) BS scheme that utilizes a spatial feature extraction technique as a preprocessing step, followed by the clustering of the mutual information (MI) of spectral bands for enhancing the efficiency of the BS. Through the SSMI BS scheme, a sharp 'bell'-shaped accuracy-dimensionality characteristic that peaks at about 20 bands has been observed for the very first time. The performance of the proposed SSMI BS scheme has been validated through 6 hyperspectral imaging (HSI) datasets (Indian Pines, Botswana, Barrax, Pavia University, Salinas, and Kennedy Space Center (KSC)), and its classification accuracy is shown to be approximately 10% better than seven state-of-the-art BS schemes (Saliency, HyperBS, SLN, OCF, FDPC, ISSC, and Convolution Neural Network (CNN)). The present result confirms that the high efficiency of the BS scheme is essentially important to observe and validate the Hughes' phenomenon in the analysis of HSI data. Experiments also show that the classification accuracy can be affected by as much as approximately 10% when a single 'crucial' band is included or missed out for classification.

Design of a Tunable Snapshot Multispectral Imaging System through Ray Tracing Simulation.

Research on snapshot multispectral imaging has been popular in the remote sensing community due to the high demands of video-rate remote sensing system for various applications. Existing snapshot multispectral imaging techniques are mainly of a fixed wavelength type, which limits their practical usefulness. This paper describes a tunable multispectral snapshot system by using a dual prism assembly as the dispersion element of the coded aperture snapshot spectral imagers (CASSI). Spectral tuning is achieved by adjusting the air gap displacement of the dual prism assembly. Typical spectral shifts of about 1 nm at 400 nm and 12 nm at 700 nm wavelength have been achieved in the present design when the air-gap of the dual prism is changed from 4.24 mm to 5.04 mm. The paper outlines the optical designs, the performance, and the pros and cons of the dual-prism CASSI (DP-CASSI) system. The performance of the system is illustrated by TraceProTM ray tracing, to allow researchers in the field to repeat or to validate the results presented in this paper.