Curvelet Transform based Denoising of Multispectral Remote Sensing Images

With the advent of sensor technology, the exertion of multispectral image (MSI) is comely omnipresent. Denoising is an essential quest in multispectral image processing which further improves recital of unmixing, classification and supplementary ensuing praxis. Explication and ocular analysis are essential to extricate data from remote sensing images for broad realm of supplications. This paper describes curvelet transform based denoising of multispectral remote sensing images. The implementation of curvelet transform is done by using both wrapping function and unequally spaced fast Fourier transform (USFFT) and they diverge in selection of spatial grid which is used to construe curvelets at every orientation and scale. The coefficients of curvelets are docket by a scaling factor, angle and spatial location criterion. This paper crisps on denoising of Linear Imaging Self Scanning Sensor (LISS) III images. The proposed denoising approach has also been collated with some existing schemes for assessment. The efficacy of proposed approach is analyzed with calculation of facet matrices such as Peak signal to noise ratio and Structural similarity at distinct variance of noise..

Estimating Gini Coefficient from Grouped Data Based on Shape-Preserving Cubic Hermite Interpolation of Lorenz Curve

The Lorenz curve and Gini coefficient are widely used to describe inequalities in many fields, but accurate estimation of the Gini coefficient is still difficult for grouped data with fewer groups. We proposed a shape-preserving cubic Hermite interpolation method to approximate the Lorenz curve by maximizing or minimizing the strain energy or curvature variation energy of the interpolation curve, and a method to estimate the Gini coefficient directly from the coefficients of the interpolation curve. This interpolation method can preserve the essential requirements of the Lorenz curve, i.e., non-negativity, monotonicity, and convexity, and can estimate the derivatives at intermediate points and endpoints at the same time. These methods were tested with 16 grouped quintiles or unequally spaced datasets, and the results were compared with the true Gini coefficients calculated with all census data and results estimated with other methods. Results indicate that the maximum strain energy interpolation method generally performs the best among different methods, which is applicable to both equally and unequally spaced grouped datasets with higher precision, especially for grouped data with fewer groups.

A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracy

Intra-individual processes are thought to continuously unfold across time. For equally spaced time intervals, the discrete-time lag-1 vector autoregressive (VAR(1)) model and the continuous-time Ornstein–Uhlenbeck (OU) model are equivalent. It is expected that by taking into account the unequal spacings of the time intervals in real data between observations will lead to an advantage for the OU in terms of predictive accuracy. In this paper, this is claim is being investigated by comparing the predictive accuracy of the OU model to that of the VAR(1) model on typical ESM data obtained in the context of affect research. It is shown that the VAR(1) model outperforms the OU model for the majority of the time series, even though time intervals in the data are unequally spaced. Accounting for measurement error does not change the result. Deleting large abrupt changes on short time intervals (that may be caused by externally driven events) does however lead to a significant improvement for the OU model. This suggests that processes in psychology may be continuously evolving, but that there are factors, like external events, which can disrupt the continuous flow.

Claxtonia goni, a new species of Tardigrada (Heterotardigrada, Echiniscidae) from the island of Maui (Hawaiian Islands, U.S.A., North Pacific Ocean), with notes to the genus Claxtonia Gąsiorek & Michalczyk, 2019

A new Tardigrada species, Claxtonia goni sp. nov. is described from specimens collected in the central area of the Haleakalā National Park, the island of Maui, Hawaii, U.S.A. The new species and Clx. pardalis (Degma & Schill, 2015) together with several examples of Clx. wendti (Richters, 1903) are the only known Claxtonia species with the plates having an intracuticular pattern resembling that on a leopard’s fur. Claxtonia goni sp. nov. differs from Clx. pardalis in the absence of pores on leg plates, in smaller and uniform pores on dorso-lateral plates, in very unequally spaced teeth in the dentate collar, in lesser ratio of internal cephalic cirrus and lateral cirrus A lengths, and in relatively shorter claws in fourth pair of legs. The differences between the new species and the other congeners as well as Echiniscus species with the same cirri composition and similar cuticular sculpture are also defined. The diagnosis of the genus Claxtonia is amended and three Echiniscus species are transferred into the genus with the proposed new combinations: Claxtonia aliquantilla (Grigarick, Schuster & Nelson, 1983) comb. nov., Clx. mosaica (Grigarick, Schuster & Nelson, 1983) comb. nov. and Clx. nigripustula (Horning, Schuster & Grigarick, 1978) comb. nov..