In the mammalian brain, the retina and LGN compress the visual input into an efficient contrastcoded representation using center-surround contrast filters that are radially symmetric (which can be nicely approximated by the difference of two Gaussians, Enroth-Cugell & Robson, 1966; Young, 1987). Then area V1 encodes orientation and other features building upon this basic contrast-enhanced input...

The concept of a loss-less data compression coding method is proposed, and a detailed description of each of its steps follows. Using the Calgary Corpus and Wikipedia data as the experimental samples and compared with existing algorithms, like PAQ or PPMstr, the new coding method could not only compress the source data, but also further re-compress the data produced by the other compression alg...

There are many ways to encode, represent, and compress satellite images. Today, with the huge technological advance, algorithms are used to perform many calculations to compress and decompress a satellite image. The future of the compression can take place only through mathematical algorithms, and the progress of mathematical research undoubtedly will lead to an advance in image and file compre...

This paper describes a novel approach of compressing large trigram language models, which uses scalar quantization to compress log probabilities and back-off coefficients, and incremental coding to compress entry pointers. Experiments show that the new approach achieves roughly 2.5 times of compression ratio compared to the well-known tree-bucket format while keeps the perplexity and accessing ...

In this paper, we shall propose a lossless image compression method, in which we compress an image by saving the differences between the encoding pixels and their adjacent pixels. To deal with a pixel, we refer to not only its up pixel but also its left pixel and replace the value of the pixel itself with the value of difference. The experimental results show that the method gives quite an impr...