Research groups at Rochester Institute of Technology and Carnegie Institution for Science are studying savanna
ecosystems and are using data from the Carnegie Airborne Observatory (CAO), which integrates advanced
imaging spectroscopy and waveform light detection and ranging (wLIDAR) data. This component of the larger
ecosystem project has as a goal the fusion of imaging spectroscopy and wLIDAR data in order to improve
per-species structural parameter estimation. Waveform LIDAR has proven useful for extracting high vertical
resolution structural parameters, while imaging spectroscopy is a well-established tool for species classification.
We evaluated data fusion at the feature level, using a stepwise discrimination analysis (SDA) approach with
feature metrics from both hyperspectral imagery (HSI) and wLIDAR data. It was found that fusing data with
the SDA improved classification, although not significantly. The principal component analysis (PCA) provided
many useful bands for the SDA selection, both from HSI and wLIDAR. The overall classification accuracy was
68% for wLIDAR, 59% for HSI, and 72% for the fused data set. The kappa accuracy achieved with wLIDAR
was 0.49, 0.36 for HSI, and 0.56 for both modalities.
Nowadays, multi-domain vertical alignment (MVA) LCD technology is becoming the mainstream approach for LCTV
industry due to its high contrast ratio and wide viewing angle property. However, like many other types of LCD devices,
MVA still has the problem of color shift, namely color washout, between normal and oblique viewing angle. In
particular, MVA shows an evident gamma curve distortion at large oblique viewing angle. This paper formulates the
MVA LCTV color performance in two stages. First, an in-depth LCD characterization was performed on an MVA
LCTV with consideration of spectral characteristic, backlight leakage, sub-pixel crosstalk, primary shift. Also,
micrograph based sub-pixel analysis was employed and suggested that the off-axis color shift problem of MVA can be
improved by using dual sub-pixel technology. Next, a generic LCD color model was proposed to relate the RGB input
with the output tristimulus value in XYZ. Sub-pixel based image rendering was performed and the results show the
feasibility of LCD color prediction with high colorimetric accuracy both at on-axis and off-axis viewing condition by
using the proposed generic color model.