Computational methods to produce enhanced images out of given SNOM raw data.

We propose to produce enhanced images out of given raw data read out by SNOM through (i) improved image formation from the raw data; (ii) wavelet de-noising of the image; and (iii) resolution enhancement by deconvolution. Our methods of improvement are based on refined models for the reduction of noise present in SNOM images and on a linear model for the imaging process. They are successfully demonstrated on (magneto-)optical SNOM images of suitable test samples, but yet they are applicable to other scanning probe microscopy techniques.

[State of the dentition in 3--10 years old children in the Munich region]. / Bestandsaufnahme des Gebisszustandes 3--10 jähriger Kinder im Raum München.

A questionnaire was sent to the parents of 1000 3- to 7-year-old children in and around Munich whose teeth we had examined. We inquired as to the oral hygiene and the socioeconomic conditions. The def and DMF mean values were evaluated according to the age group. The results indicate that the condition of the teeth of our young people can only be improved if measures for dental hygiene and caries prophylaxis in general are intensified and improved at the kindergarten level.