Juris Siņica- Siņavskis

Elektronikas un datorzinātņu institūts

The article proposes two novel and relatively simple unsupervised procedures for the selection of informative small subsets of spectral bands in hyperspectral images. To ensure the informativeness of the subsets, bands featuring higher entropy are included. The correlation of band images is restricted to avoid redundancy of the subsets. The entropy...

The paper is focused on problems related to proper selection of relatively small number of bands from hyperspectral images ensuring sufficiently accurate classification of pixels into several defined categories. Two approaches to construction of the set of spectral bands are presented. To select the most informative bands, their entropy and mutual...

The paper addresses problems related to classification of images obtained by various types of remote sensing devices. Development and use of Bayes type land cover classifiers based on multidimensional Gaussian, Dirichlet and gamma distributions is analysed and compared on the basis of sample data from RGB and hyperspectral thermal sensing devices w...

The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derive...

The paper is focused on the analysis of classification possibilities of multisensor data with different spatial resolutions using combined classifiers based on Bayes approach with equal prior probabilities and on minimum of the Mahalanobis distance. The task set up for the 2014 IEEE GRSS Data Fusion Contest was chosen as an application example. Hig...

A simplified approach to classification of multispectral image fragments by their specific spectral features is presented. Application of this approach to discrimination of vegetation areas occupied by the Giant Hogweed species is described and compared with an approach based on calculation of the Consolidated Covariance Image. The proposed method...

The paper discusses the properties of a two-stage Bayes classifier construction method in a case when the objects are represented with two quantitative features. The aim of the study was to show that, in general, the two-stage approach allows one to enhance the precision of the classification results. The main method of the investigation is statist...

This work describes the task of inventorying Baltic mixed forests at an individual tree level. The development of a practicable methodology for semi-automated identification of tree species was targeted. Data acquisition equipment and preprocessing software, explored forest area, processing approaches, obtained classification results as well as new...

This work describes the task of inventorying Baltic mixed forests at an individual tree level. The development of a practicable methodology for semi-automated identification of tree species was targeted. Data acquisition equipment and preprocessing software, explored forest area, processing approaches, obtained classification results as well as new...

The paper addresses solution of the specific application task, namely, classification of individual trees to 5 conifer and deciduous species in mixed Baltic forest, based on processing of airborne hyperspectral and LiDAR data. Description of instruments and software used for data acquisition and preprocessing, image processing approach, obtained cl...

The paper is devoted to the applied problem of tree species classification from multispectral data obtained within aircraft overflight of the particular forest area. Theoretical background for solving the task is substantiated. Four versions of classifiers were considered and experimentally tested. Two of them, namely Bayes classifier and a classif...

A. Lorencs, J. Sinica-Sinavskis. One Method of Image Processing and its Numerical Analysis // Electronics and Electrical Engineering. - Kaunas: Technologija, 2010. - No. 7(103). - P. 25-30. The paper discusses application of linear regression models to image transformation and pattern recognition, oriented towards creation of technology for fast pr...

The problem of detecting specific objects or anomalies (OA) in tissue samples of living beings from their digital images is considered. Taking into account that pixel values in images (brightness levels) can be interpreted as sums of values related to physical objects and realizations of additive random variables, regression method (RM) for detecti...