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This paper has two achievements. The first aim of this paper is optimization of the lossy compression coder realized as companding quantizer with optimal compression law. This optimization is achieved by optimizing maximal amplitude for that optimal companding quantizer for Laplacian source. Approximate expression in closed form for optimal maximal amplitude is found. Although this expression is very simple and suitable for practical implementation, it satisfy optimality criterion for Lloyd-Max quantizer (for R >= 6 bits/sample). In the second part of this paper novel simple lossless compression method is presented. This method is much simpler than Huffman method, but it gives better results. Finally, at the end of the paper, we join optimal companding quantizer and lossless coding method together in one generalized compression method. This method is applied on the concrete still image and good results are obtained. Besides still images, this method also could be used for compression speech and bio-medical signals.

In this paper an algorithm for grayscale image compression is presented, based on implementation of forward adaptive quantizers designed for signals with discrete amplitudes. Experiments are done, applying this algorithm on standard grayscale images and obtained results show that significant reduction of the bit-rate can be achieved (about 40%), maintaining very high quality of the reconstructed image, i.e. near lossless compression is performed. Ill. 2, bibl. 6, tabl. 2 (in English; abstracts in English and Lithuanian).

The aim of this paper is to improve the G.711 standard, which is widely used, especially in the public switched telephone network (PSTN). Two solutions are proposed. The first solution uses only lossless coder, achieving a bit-rate decrease of 0.82 bits/sample, compared to the G.711 codec. The second solution uses forward adaptation and a lossless coder, further decreasing the bit-rate (by 1.25 bits/sample) and achieving higher average signal-to-quantization noise ratio (SQNR) in comparison with the G.711 codec. Also, the second solution is more robust than the G.711 codec, which means that it has near constant SQNR for a wide range of input signal power. That is very important for signals whose input power varies with time, such as speech and video signals. Our solutions are compatible with the G.711 codec, they have little additional complexity and delay and therefore can be applied in real-time systems, such as PSTN or VoIP. They can also be used in many other systems, such as WiMax and OFDM, as a replacement or improvement of the G.711 codec. Standardization process of the G.711.1 standard (which is a wide-band extension of the G.711 standard) is largely present. Our solutions fulfill all the requirements for that new standard; therefore they can be implemented in its low-frequency part.

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