scholarly journals AN ALGORITHM FOR GENERATING NATURAL COLOR IMAGES FROM FALSE COLOR USING SPECTRAL TRANSFORMATION TECHNIQUE WITH HIGHER POLYNOMIAL ORDER

Author(s):  
S. Kala ◽  
A. Kumar ◽  
A. K. Joshi ◽  
V. M. Bothale ◽  
B. G. Krishna

<p><strong>Abstract.</strong> Satellite imageries in True color composite or Natural Color composite (NCC) serves the best combination for visual interpretation. Red, Green and Infrared channels form false color composite which might not be as useful as NCC to a non-remote sensing professional. As blue band is affected by large atmospheric scattering, satellites like IRS-LISS IV, SPOT do not have blue band. To generate NCC from such satellite data blue band must be simulated. Existing algorithms of spectral transformation do not provide robust coefficients leading to wrong NCC colors especially in water bodies. To achieve more robust coefficients, we have proposed new algorithm to generate NCC for IRS-LISS IV data using second order polynomial regression technique. Second order polynomial transformation functions consider even minor variability present in the image as compared to 1st order so that the derived coefficients are adjustable to accommodate spatial and temporal variability while generating NCC. In this study, Sentinel-2 image was used for deriving coefficients with blue band as dependent and green, red and infrared as independent variables. Simulated Sentinel band showed high accuracy with correlation of 0.93 and 0.97 for two test sites. Using the same coefficients, blue band was simulated for LISS-IV which also showed good correlation of 0.90 with sentinel original blue band. On comparing LISS-IV simulated NCC with simulated NCC from other algorithms, it was observed that higher order polynomial transformation was able to achieve higher accuracy especially for water bodies where expected color is green. Thus, proposed algorithms can be used for transforming false color image to natural color images.</p>

Author(s):  
S. B. Sayyad ◽  
Z. R. Mohammed ◽  
R. R. Deshmukh

<p><strong>Abstract.</strong> The imaging spectroscopy offers an opportunity to map and discriminate different minerals on the lunar surface which further helps to understand the origin, evolution process, and the crustal composition on the surface of the moon. Compositional mapping of the lunar surface is considered as a standard approach for mineral mapping. This paper reports surface mineralogy of the lunar surface from Mare Vaporum using Chandrayaan-1 Hyperspectral remotely sensed data from HySi sensor. False color composite is created using different band shaping algorithms like band strength; band curve and band tilt parameters at crucial wavelength for spatial analysis. The Spectral analysis has been done by deriving reflectance spectra at varying locations from the area under study. The Study shows the mineral map with different categories of minerals which are high-Ca pyroxene and/or olivine and low Ca-pyroxene. However because of the limited spectral coverage of HySi, data at the longer wavelengths required to discriminate among different group of minerals.</p>


Author(s):  
Winda Kusuma Dewi ◽  
Choirul Anam ◽  
Eko Hidayanto ◽  
Annisa Lidia Wati ◽  
Geoff Dougherty

Abstract The study aims to correlate the effective diameter (Deff) and water-equivalent diameter (Dw) parameters with anterior–posterior (AP), lateral (LAT) and AP + LAT dimensions in order to estimate the patient dose in head CT examinations. Seventy-four patient datasets from head CT examinations were retrospectively collected. The patient’s sizes were calculated from the middle slice using a software of IndoseCT. Dw and Deff were plotted as functions of AP, LAT and AP + LAT dimensions. The best trendline fit for LAT and AP functions was a second order polynomial, which resulted in R2 of 0.89 for Deff vs LAT, 0.88 for Dw vs LAT, 0.92 for Deff vs AP and 0.91 for Dw vs AP. A linear correlation was found for Deff vs AP + LAT, Dw vs AP + LAT and Dw vs Deff with R2 of 0.97, 0.96 and 0.98, respectively.


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