Caries status in 16 year-olds with varying exposure to water fluoridation in Ireland

Most of the Republic of Ireland's public water supplies have been fluoridated since the mid-1960s while Northern Ireland has never been fluoridated, apart from some small short-lived schemes in east Ulster.

OBJECTIVE

This study examines dental caries status in 16 year-olds in a part of Ireland straddling fluoridated and non-fluoridated water supply areas and compares two methods of assessing the effectiveness of water fluoridation. The cross-sectional survey tested differences in caries status by two methods: 1, Estimated Fluoridation Status as used previously in national and regional studies in the Republic and in the All-Island study of 2002; 2, Percentage Lifetime Exposure, a modification of a system described by Slade in 1995 and used in Australian caries research.

METHODS

Adolescents were selected for the study by a two-part random sampling process. Firstly, schools were selected in each area by creating three tiers based on school size, and selecting schools randomly from each tier. Then random sampling of 16-year-olds from these schools, based on a pre-set sampling fraction for each tier of schools.

RESULTS

With both systems of measurement, significantly lower caries levels were found in those children with the greatest exposure to fluoridated water when compared to those with the least exposure.

CONCLUSIONS

The survey provides further evidence of the effectiveness in reducing dental caries experience up to 16 years of age. The extra intricacies involved in using the Percentage Lifetime Exposure method did not provide much more information when compared to the simpler Estimated Fluoridation Status method.

Fast reconstruction of subband-decomposed progressively transmitted signals

We propose a fast reconstruction method for a subband-decomposed, progressive signal coding system. We show that unlike the conventional approach which requires a fixed computational complexity, the computational complexity of the proposed approach is proportional to the number of refined coefficients at each level of progression. Therefore, unrefined coefficients do not add to the computational complexity of the proposed scheme. It is shown, through specific examples, that the proposed approach can lead to significant reductions in reconstruction complexity. Furthermore, the proposed approach provides the capability for an online updating of the reconstructed image based on receiving the refinement of each coefficient.

Adaptive image coding using spectral classification

We present a new classification scheme, dubbed spectral classification, which uses the spectral characteristics of the image blocks to classify them into one of a finite number of classes. A vector quantizer with an appropriate distortion measure is designed to perform the classification operation. The application of the proposed spectral classification scheme is then demonstrated in the context of adaptive image coding. It is shown that the spectral classifier outperforms gain-based classifiers while requiring a lower computational complexity.

Comparison of different methods of classification in subband coding of images

This paper investigates various classification techniques, applied to subband coding of images, as a way of exploiting the nonstationary nature of image subbands. The advantages of subband classification are characterized in a rate-distortion framework in terms of "classification gain" and overall "subband classification gain." Two algorithms, maximum classification gain and equal mean-normalized standard deviation classification, which allow unequal number of blocks in each class, are presented. The dependence between the classification maps from different subbands is exploited either directly while encoding the classification maps or indirectly by constraining the classification maps. The trade-off between the classification gain and the amount of side information is explored. Coding results for a subband image coder based on classification are presented. The simulation results demonstrate the value of classification in subband coding.

A perceptually motivated three-component image model-part II: applications to image compression

For past I see ibid., vol.4, no.4, p.405 (1995). The use of the image model of Part I is investigated in the context of image compression. The model decomposes the image into a primary component that contains the strong edge information, a smooth component that represents the background slow-intensity variations, and a texture component that contains the textures. The primary component, which is known to be perceptually important, is encoded separately by encoding the intensity and geometric information of the strong edge brim contours. Two alternatives for coding the smooth and texture components are studied: entropy-coded adaptive DCT and entropy-coded subband coding. It is shown via simulations that the proposed schemes, which can be thought of as a hybrid of waveform coding and feature-based coding techniques, result in both subjective and objective performance improvements over several other image coding schemes and, in particular, over the JPEG continuous-tone image compression standard. These improvements are especially noticeable at low bit rates. Furthermore, it is shown that a perceptual tuning based on the contrast-sensitivity of the human visual system can be used in the DCT-based scheme, which in conjunction with the three-component model, leads to additional subjective performance improvements.

Three-dimensional subband coding of video

We describe and show the results of video coding based on a three-dimensional (3-D) spatio-temporal subband decomposition. The results include a 1-Mbps coder based on a new adaptive differential pulse code modulation scheme (ADPCM) and adaptive bit allocation. This rate is useful for video storage on CD-ROM. Coding results are also shown for a 384-kbps rate that are based on ADPCM for the lowest frequency band and a new form of vector quantization (geometric vector quantization (GVQ)) for the data in the higher frequency bands. GVQ takes advantage of the inherent structure and sparseness of the data in the higher bands. Results are also shown for a 128-kbps coder that is based on an unbalanced tree-structured vector quantizer (UTSVQ) for the lowest frequency band and GVQ for the higher frequency bands. The results are competitive with traditional video coding techniques and provide the motivation for investigating the 3-D subband framework for different coding schemes and various applications.

A perceptually motivated three-component image model-Part I: description of the model

Some psychovisual properties of the human visual system are discussed and interpreted in a mathematical framework. The formation of perception is described by appropriate minimization problems and the edge information is found to be of primary importance in visual perception. Having introduced the concept of edge strength, it is demonstrated that strong edges are of higher perceptual importance than weaker edges (textures). We have also found that smooth areas of an image influence our perception together with the edge information, and that this influence can be mathematically described via a minimization problem. Based on this study, we have proposed to decompose the image into three components: (i) primary, (ii) smooth, and (iii) texture, which contain, respectively, the strong edges, the background, and the textures. An algorithm is developed to generate the three-component image model, and an example is provided in which the resulting three components demonstrate the specific properties as expected. Finally, it is shown that the primary component provides a superior representation of the strong edge information as compared with the popular Laplacian-Gaussian operator edge extraction scheme.