Technical Note: Measurement of the tropical UTLS composition in presence of clouds using millimetre-wave heterodyne spectroscopy

The MARSCHALS (Millimetre-wave Airborne Receiver for Spectroscopic CHaracterisation of Atmospheric Limb-Sounding) project has the general objectives of demonstrating the measurement capabilities of a limb viewing instrument working in the millimetre and sub-millimetre spectral regions (from 294 to 349 GHz) for the study of the Upper Troposphere – Lower Stratosphere (UTLS). MARSCHALS has flown on board the M-55 stratospheric aircraft (Geophysica) in two measurements campaigns. Here we report the results of the analysis of MARSCHALS measurements during the SCOUT-O3 campaign held in Darwin (Australia) in December 2005 obtained with MARC (Millimetre-wave Atmospheric-Retrieval Code). MARSCHALS measured vertical distributions of temperature, water vapour, ozone and nitric acid in the altitude range from 10 to 20 km in presence of clouds that obscure measurements in the middle infrared spectroscopic region. The minimum altitude at which the retrieval has been possible is determined by the high water concentration typical of the tropical region rather than the extensive cloud coverage experienced during the flight. Water has been measured from 10 km to flight altitude (~18 km) with a 10% accuracy, ozone from 14 km to flight altitude with accuracy ranging from 10% to 60%, while the retrieval of nitric acid has been possible with an accuracy not better than 40% only from 16 km to flight altitude due to the low signal to noise ratio of its emission in the analysed spectral region. The results have been validated using measurement made in a less cloudy region by MIPAS-STR, an infrared limb-viewing instrument on board the M-55, during the same flight

Technical Note: Measurement of the tropical UTLS composition in presence of clouds using millimetre-wave heterodyne spectroscopy

The MARSCHALS (Millimetre-wave Airborne Receiver for Spectroscopic CHaracterisation of Atmospheric Limb-Sounding) project has the general objectives of demonstrating the measurement capabilities of a limb viewing instrument working in the millimetre and sub-millimetre spectral regions (from 294 to 349 GHz) for the study of the Upper Troposphere – Lower Stratosphere (UTLS). MARSCHALS has flown on board the M-55 stratospheric aircraft (Geophysica) in two measurements campaigns. Here we report the results of the analysis of MARSCHALS measurements during the SCOUT-O3 campaign held in Darwin (Australia) in December 2005 obtained with MARC (Millimetrewave Atmospheric-Retrieval Code). MARSCHALS measured vertical distributions of temperature, water vapour, ozone and nitric acid in the altitude range from 10 to 20 km in presence of clouds that obscure measurements in the middle infrared spectroscopic region. The minimum altitude at which the retrieval has been possible is determined by the high water concentration typical of the tropical region rather than the extensive cloud coverage experienced during the flight. Water has been measured from 10 km to flight altitude (~18 km) with a 10% accuracy, ozone from 14 km to flight altitude with accuracy ranging from 10% to 60%, while the retrieval of nitric acid has been possible with an accuracy not better than 40% only from 16 km to flight altitude due to the low signal to noise ratio of its emission in the analysed spectral region. The results have been validated using measurement made in a less cloudy region by MIPAS-STR, an infrared limb-viewing instrument on board the M-55, during the same flight

An improved H.263 video coder relying on weighted median filtering of motion vectors

The impact of a regularization of motion vectors (MVs) on the performance of a block-DCT based video coder (H.263) is addressed. Postprocessing is accomplished by exploiting both the spatial correlation of the vector field and the confidence of the estimated block vectors. A previously proposed adaptive scheme for MV smoothing, based on the theory of vector median filters, is adjusted and embedded into an H.263 coder. With a bit stream that is perfectly H.263-compatible, results are improved, especially for very low bit rates and complex motion of the scen

Full scale assessment of pansharpening methods and data products

Quality assessment of pansharpened images is traditionally carried out either at degraded spatial scale by checking the synthesis property of Wald's protocol or at the full spatial scale by separately checking the spectral and spatial consistencies. The spatial distortion of the QNR protocol and the spectral distortion of Khan's protocol may be combined into a unique quality index, referred to as hybrid QNR (HQNR), that is calculated at full scale. Alternatively, multiscale measurements of indices requiring a reference, like SAM, ERGAS and Q4, may be extrapolated to yield a quality measurement at the full scale of the fusion product, where a reference does not exist. Experiments on simulated Pléiades data, of which reference originals at full scale are available, highlight that quadratic polynomials having three-point support, i.e. fitting three measurements at as many progressively doubled scales, are adequate. Q4 is more suitable for extrapolation than ERGAS and SAM. The Q4 value predicted from multiscale measurements and the Q4 value measured at full scale thanks to the reference original, differ by very few percents for six different state-of-The-art methods that have been compared. HQNR is substantially comparable to the extrapolated Q4

Near-lossless compression of hyperspectral data through classified spectral prediction

This paper presents a novel scheme for lossless/near-lossless hyperspectral image compression, that exploits a classified spectral prediction. MMSE spectral predictors are calculated for small spatial blocks of each band and are classified (clustered) to yield a user-defined number of prototype predictors for each wavelength, capable of matching the spatial features of different classes of pixel spectra. Unlike most of the literature, the proposed method employs a purely spectral prediction, that is suitable for compressing the data in band-interleaved-by-line (BIL) format, as they are available at the output of the on-board spectrometer. In that case, the training phase, i.e., clustering of predictors for each wavelength, may be moved off-line. Thus, prediction will be slightly less fitting, but the overhead of predictors calculated on-line is saved. Although prediction is purely spectral, hence ID, spatial correlation is removed by the training phase of predictors, aimed at finding statistically homogeneous spatial classes matching the set of prototype spectral predictors. Experimental results on AVIRIS data show improvements over the most advanced methods in the literature, with a computational complexity far lower than that of analogous methods by other authors