Spatial and Spectral Separability of Grasslands in the inner Turku Archipelago using Landsat Thematic Mapper Satellite Imagery

The present study investigates the spatial and spectral discrimination potential for grassland patches in the inner Turku Archipelago using Landsat Thematic Mapper satellite imagery. The spatial discrimination potential was computed through overlay analysis using official grassland parcel data and a hypothetical 30 m resolution satellite image capturing the site. It found that Landsat TM imagery’s ability to retrieve pure or near-pure pixels (90% purity or more) from grassland patches smaller than 1 hectare was limited to 13% success, compared to 52% success when upscaling the resolution to 10 x 10 m pixel size. Additionally, the perimeter/area patch metric is proposed as a predictor for the suitability of the spatial resolution of input imagery. Regression analysis showed that there is a strong negative correlation between a patch’s perimeter/area ratio and its pure pixel potential. The study goes on to characterise the spectral response and discrimination potential for the five main grassland types occurring in the study area: recreational grassland, traditional pasture, modern pasture, fodder production grassland and overgrown grassland. This was done through the construction of spectral response curves, a coincident spectral plot and a contingency matrix as well as by calculating the transformed divergence for the spectral signatures, all based on training samples from the TM imagery. Substantial differences in spectral discrimination potential between imagery from the beginning of the growing season and the middle of summer were found. This is because the spectral responses for these five grassland types converge as the peak of the growing season draws nearer. Recreational grassland shows a consistent discrimination advantage over other grassland types, whereas modern pasture is most easily confused. Traditional pasture land, perhaps the most biologically valuable grassland type, can be spectrally discriminated from other grassland types with satisfactory success rates provided early growing season imagery is used.

Evaluation of group electronegativities and hardness (softness) of group 14 elements and containing functional groups through density functional theory and correlation with NMR spectra data

Quantum Chemical calculations for group 14 elements of Periodic Table (C, Si, Ge, Sn, Pb) and their functional groups have been carried out using Density Functional Theory (DFT) based reactivity descriptors such as group electronegativities, hardness and softness. DFT calculations were performed for a large series of tetracoordinated Sn compounds of the CH3SnRR'X type, where X is a halogen and R and R' are alkyl, halogenated alkyl, alkoxy, or alkyl thio groups. The results were interpreted in terms of calculated electronegativity and hardness of the SnRR'X groups, applying a methodology previously developed by Geerlings and coworkers (J. Phys. Chem. 1993, 97, 1826). These calculations allowed to see the regularities concerning the influence of the nature of organic groups RR' and inorganic group X on electronegativities and hardness of the SnRR'X groups; in this case, it was found a very good correlation between the electronegativity of the fragment and experimental 119Sn chemical shifts, a property that sensitively reflects the change in the valence electronic structure of molecules. This work was complemented with the study of some compounds of the EX and ER types, where E= C, Si, Ge, Sn and R= CH3, H, which was performed to study the influence that the central atom has on the electronegativity and hardness of molecules, or whether these properties are mainly affected for the type of ligand bound to the central atom. All these calculations were performed using the B3PW91 functional together with the 6-311++G** basis set level for H, C, Si, Ge, F, Cl and Br atoms and the 3-21G for Sn and I atoms.

Examining the Role of Rebranding in Perceived Image of a Product Line

The main objective for this study was to explore certain organization’s product line rebranding process and its impact on product line’s perceived image. The case company is a global paper, packaging and forest products company, business segment paper board. The audience explored is one of the company’s major customers, merchant in Germany. The research was performed as a descriptive case study with a purpose to provide longitudinal insight into the product line image and its eventual alteration as a result of the case company’s rebranding process. Mainly qualitative methods were used for conducting the research. The data for the empirical part was collected with a web-based survey at two different points of time; before the rebranded products entered the market and after they had been available approximately six months. The results of this study reveal that the case company has performed well in its attempt to improve product line’s brand image through rebranding. It was found that between the two brand image measurements the product brand image seems to have improved in all of the areas which according to theoretical framework of this study contribute to formation of brand image; brand associations, marketing communications and interpersonal relationships, not forgetting the original platform that initiated the change; technical quality modifications. In other words it may be concluded that as technical quality was brought to a new level, also assessments about the brand image improved respectively.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/10 (N11).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/02 (N3).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/08 (N8).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/06 (N7).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/03 (N4).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/01 (N2).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1896/12 (N1).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/05 (N6).

L'Image : revue artistique et littéraire ornée de figures sur bois, paraissant tous les mois / [secrétaire de la rédaction, Jules Rais ; administrateur, Tony Beltrand]

1897/09 (N10).

Detection of beetle damage in forests by X-ray CT image processing

Some beetle species can have devastating economic impacts on forest and nursery industries. A recent example is Anophophora glabripennis, a species of beetle known in the United States as the ''Asian Longhorrned beetle'', which has damaged many American forests, and is a threat which can unintentionally reach south American countries, including Brazil. This work presents a new method based on X-ray computerized tomography (CT) and image processing for beetle injury detection in forests. Its results show a set of images with correct identification of the location of beetles in living trees as well as damage evaluation with time.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.