In this paper, a problem of resource expenses needed for storage, processing and transferring a large number of high resolution digital remote sensing images is considered. Application of discrete atomic compression (DAC), which is an algorithm based on atomic wavelets, to solving this problem is studied. Dependence of efficiency of the DAC algorithm on its parameters, in particular, quality loss settings, a structure of discrete atomic transform, which is a core of DAC, and a method of quantized wavelet coefficients’ encoding, is investigated. Binary arithmetic coding and a combination of Huffman codes with run-length encoding are used to provide lossless compression of quantized atomic wavelet coefficients. Comparison of these methods is presented. A set of digital images of the European Space Agency is employed as test data. In addition, we discuss promising ways to improve the DAC algorithm.
One of distinguishing features of the present is the explosive increase in data amount including digital images such as satellite remote sensing images. Processing, storing and transmission via networks of a huge number of digital images requires considerable resources in the sense of memory, time, computational power, etc. In this regard, the importance of image compression is growing and the development of novel compression techniques that would satisfy new requirements, for instance, to security and level of privacy protection continues. Atomic wavelets and their generalizations can be a useful tool for this. They are constructed using atomic functions, which are compactly supported solutions of special functional differential equations. Discrete atomic transform (DAT), which is a process of computation of expansion coefficients of the function describing the source discrete data, is applied in discrete atomic compression (DAC). DAC can be applied to compression of full color digital images, as well as monocomponent ones. In this paper, we investigate efficiency, which is measured by compression ratio (CR), of satellite image compression using DAC and the corresponding loss of quality measured by several quantitative criteria. They are maximum absolute deviation (MAD), root mean square (RMS) and peak signal-to-noise ratio (PSNR). We show that DAC provides near lossless compression, when quality loss is minor in a sense of the MAD-metric. Also, it is proved that using DAC it is possible to obtain better compression than by applying JPEG with the same quality of the obtained results.
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