&lt;title&gt;FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression&lt;/title&gt;

Abstract-Compression is a relatively new introduced technique for seismic data operations. The main drive behind the use of data compression in seismic data is the very large size of seismic data acquired. Some of the most recent acquired marine seismic data sets exceed 10 Tbytes, and in fact there are currently seismic surveys planned with a volume of around 120 Tbytes. Thus, the need to compress these very large seismic data files is imperative. Nevertheless, seismic data are quite different from the typical images used in image processing and multimedia applications. Some of their major differences are the data dynamic range exceeding 100 dB in theory, very often it is data with extensive oscillatory nature, the and directions represent different physical meaning, and there is significant amount of coherent noise which is often present in seismic data. Up to now some of the algorithms used for seismic data compression were based on some form of wavelet or local cosine transform, while using a uniform or quasiuniform quantization scheme and they finally employ a Huffman coding scheme. Using this family of compression algorithms we achieve compression results which are acceptable to geophysicists, only at low to moderate compression ratios. For higher compression ratios or higher decibel quality, significant compression artifacts are introduced in the reconstructed images, even with high-dimensional transforms. The objective of this paper is to achieve higher compression ratio, than achieved with the wavelet/uniform quantization/Huffman coding family of compression schemes, with a comparable level of residual noise. The goal is to achieve above 40 dB in the decompressed seismic data sets. Several established compression algorithms are reviewed, and some new compression algorithms are introduced. All of these compression techniques are applied to a good representation of seismic data sets, and their results are documented in this paper. One of the conclusions is that adaptive multiscale local cosine transform with different windows sizes performs well on all the seismic data sets and outperforms the other methods from the SNR point of view. All the described methods cover wide range of different data sets. Each data set will have his own best performed method chosen from this collection. The results were performed on four different seismic data sets. Special emphasis was given to achieve faster processing speed which is another critical issue that is examined in the paper. Some of these algorithms are also suitable for multimedia type compression.

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“…This compression, which is based on uniform (scalar) quantization [7], [20], [21], [25], has three steps.…”

Section: Methods 2: Fast Wavelet Compression With Uniform Quantizmentioning

confidence: 99%

Low bit-rate efficient compression for seismic data

Averbuch

Meyer

Strömberg

et al. 2001

IEEE Trans. on Image Process.

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“…The fact is that the Fourier theory is not involved anymore and the construction of any wavelet system lies only in the spatial domain. If the explanation of the theory relies on the works of Sweldens (Sweldens, 1995, 1996& Valens, 2004) the lifting approach has links with many other schemes (Burrus et al, 1998;Do & Vetterli, 2003Cunha et al, 2006;Lu & Do, 2007;Nguyen & Oraintara, 2008& Brislawn, 2010. The lifting-based wavelet transform can be seen as a succession of three operations: split, predict and update.…”

Section: Swelden's Lifting Schemementioning

confidence: 99%

“…However, since equations (28 and 29) compute one output for each two consecutive inputs, a modification needs to be made. The basic operation required here, is derived from the multirate signal processing theory (Fliege, 1994;Hankerson et al, 2005;Cunha et al, 2006;Lu & Do, 2007;Nguyen & Oraintara, 2008& Brislawn, 2010. It simply consists of using a down-sampler or decimator by a factor of two.…”

Section: Filter Banks and Wavelet Implementationsmentioning

confidence: 99%

The Wavelet Transform for Image Processing Applications

Bouden¹,

Mokhtar²

2012

Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

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“…For this process interpolation based on the B-Spline-Wavelets was used (Bradley, 1993); (Donoho, 1993); (Graps, 1995); (Revathy, 2000).…”

Section: Computer Program For 2d-and 3d-layer Visualization Of the Somentioning

confidence: 99%

Intelligent instrument to facilitate decision making in the evaluation of soil resistance to root penetration

Rabello

Cruvinel

2009

Sci. agric. (Piracicaba, Braz.)

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This contribution introduces an instrument for decision-making in agricultural processes based on the measurements and mapping of soil resistance to root penetration. Its development was based on a new and advanced instrumentation tool, enabling in almost real-time to acquire the necessary information for spatial variability analysis of plant root penetration resistance in soils, due to natural or artificial soil compaction processes, i.e., not only for an area of soil but also for a soil profile. The system allows soil resistance assays for both laboratory and agricultural fields. Moreover, the development focused on an intelligent instrumentation concept, as well as a microprobe (30º for the spire angle, 1,6 mm for the base diameter, and 30 mm of total length), with a strain-gage transducer sensor. Results have shown that measurements of soil resistance to plant root penetration can be performed up to the limit of (483.47 ± 0.69) N, with a resolution of 15.4 N. Additionally, the versatility of the system is verified for soil resistance data collection and its interpretation to root plant penetration, since they can be presented in table formats, one-dimensional graphs, two-dimensional and threedimensional maps. Therefore, this system enables users to obtain a quick interpretation of the soil aggregation state in agricultural areas.

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<title>FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression</title>

Cited by 108 publications

References 0 publications

Low bit-rate efficient compression for seismic data

Low bit-rate efficient compression for seismic data

The Wavelet Transform for Image Processing Applications

Intelligent instrument to facilitate decision making in the evaluation of soil resistance to root penetration

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