The scope of the present dissertation is a deep lossy compression of still and moving grayscale pictures while maintaining their fidelity, with a specific goal of creating a working prototype of a software system for use in low bandwidth transmission of still satellite imagery and weather briefings with the best preservation of features considered important by the end user.

Medical images, like any other digital data, require compression in order to reduce disk space needed for storage and time needed for transmission. The lossless compression methods of still images can shorten the file only to a very limited degree. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification – an inseparable feature of the fractal compression – would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression. Based on a survey of literature and own cogitations, the author attempts to provide an adapted to the needs of medical imaging solution that will overcome the unfavorable ailments of the fractal compression methods. The thesis does not provide only theoretical deliberations but also gives implementation of the proposed algorithm, which is used to test the suitability of the fractal compression to medical imaging. The results of the work are more than satisfying – the fidelity of the images compressed with the proposed fractal compression method meets the requirements imposed on the medical images and the fractal magnification outperforms other magnification techniques.

Currently living in the digital age, so the manipulation of data and images is often all day. Due to the problem of space for storage of pictures and time of transmission, many compression techniques had been developed, and a great challenge is to make these techniques to bring good results in terms of compression rate, picture quality and processing time. The Fractal Compression technique developed by Fisher, was described, implemented and tested in this work and it brought great results, and considerable improvement in terms of execution time, which was rather low. Another area that has been emphasizing is the use of biometric techniques to the people recognition. A very used technique is the iris recognition that has shown enough reliability. Thus, connecting the two technologies brings great benefits. In this work, images of iris were compressed by the method implemented here and were made simulations of the technique iris recognition developed by Libor Maseck. The results show that it is possible to compress fractally the images without damage the recognition system. Comparisons were made and was possible realize that even with changes in pixels of images, the system remains very reliable, bringing benefits to storage space. / Atualmente vive-se na era digital, por isso a manipulação de dados e imagens é freqüente todos os dias. Devido ao problema de espaço para armazenamento dessas imagens e tempo de transmissão, foram desenvolvidas várias técnicas de compressão, e um grande desafio é fazer com que essas técnicas tragam bons resultados em termos de taxa de compressão, qualidade da imagem e tempo de processamento. A técnica de compressão Fractal desenvolvida por Fisher, foi descrita, implementada e testada neste trabalho e trouxe ótimos resultados, e melhoria considerável em termos de tempo de execução, que foi bastante reduzido. Outra área que vem se destacando é o uso de técnicas biométricas para reconhecimento de pessoas. Uma técnica muito usada é o reconhecimento de íris que tem mostrado bastante contabilidade. Assim, aliar as duas tecnologias traz grandes benefícios. No presente trabalho, imagens de íris foram comprimidas pelo método aqui implementado e foram realizadas simulações da técnica de reconhecimento de íris desenvolvida por Maseck. Os resultados mostram que é possível comprimir fractalmente as imagens sem prejudicar o sistema de reconhecimento. Comparações foram realizadas e foi possível perceber que mesmo havendo mudanças nos pixels das imagens, o sistema permanece bastante confiavel, trazendo vantagens em espaço de armazenamento. / Mestre em Ciências