Interpolative Coding Research Articles

Internal conversion coefficients of high multipole transitions: Experiment and theories

A compilation of the available experimental internal conversion coefficients (ICCs), α T, α K, α L, and ratios K/L and K/LM of high multipole ( L > 2) transitions for a number of elements in the range 21 ⩽ Z ⩽ 94 is presented. Our listing of experimental data includes 194 data sets on 110 E3 transitions, 10 data sets on 6 E4 transitions, 11 data sets on 7 E5 transitions, 38 data sets on 21 M3 transitions, and 132 data sets on 68 M4 transitions. Data with less than 10% experimental uncertainty have been selected for comparison with the theoretical values of Hager and Seltzer [R.S. Hager, E.C. Seltzer, Nucl. Data Tables A 4 (1968) 1], Rosel et al. [F. Rösel, H.M. Fries, K. Alder, H.C. Pauli, At. Data Nucl. Data Tables 21 (1978) 91], and BRICC. The relative percentage deviations (%Δ) have been calculated for each of the above theories and the averages ( % Δ ¯ ) are estimated. The Band et al. [I.M. Band, M.B. Trzhaskovskaya, C.W. Nestor Jr., P.O. Tikkanen, S. Raman, At. Data Nucl. Data Tables 81 (2002) 1] tables, using the BRICC interpolation code, are seen to give theoretical ICCs closest to experimental values.

Tournament Coding of Integer Sequences

A new, simple non-statistical source coding technique for sequences of integers is suggested. The method is based on a tournament scheme, with the sequence arranged into pairs, where maxima (‘winners’) are encoded recursively, and minima are encoded by semi-fixed-length codes using the related maxima to bound the code lengths. In the experiments, tournament coding has outperformed the other non-statistical methods (gamma, delta, Fibonacci and interpolative coding) for uniform distribution of numbers. Also for non-uniform distributions the method is quite competitive.

Preparing area average rainfall on a regular grid from scattered raingauge data

The problem of obtaining the area average rainfall from scattered raingauge data on to a regular grid has been addressed. A new interpolation formula has been obtained using finite element method giving due consideration to missing observations in any raingauge station data time series. An important feature of this method is that there is no need to redesign the triangulation of the given region in case: (a) if number of observations increase in this region, or (b) if observations are missing in the data time series of any station chosen as a node in triangulating this region. Their contribution to the areal precipitation has been incorporated in a mathematically consistent manner. As an application of this method, daily rainfall time series of 119 raingauge stations for four successive summer monsoons (1986-1989) are utilized to obtain the daily precipitation values on a spatial grid with 1.8° × 3.6° (lat/lon) resolution. From the daily gridded rainfall, pentads (5-day averages) of rainfall are obtained. These pentads are arranged in a time series and a principal component analysis (PCA) is performed. The first four principal components explain 63% of the total variance of rainfall over India. The oscillations depicted by these modes agree well with earlier studies. It is concluded that a few dominant PCs of rainfall calculated from pentads (as compared to seasonal and annual average rainfall) explain a larger part of the total variance of rainfall. This method is essentially related to large-scale rainfall depiction. It could, therefore, easily be used to produce global gridded precipitation fields from raingauge measurements. The spatial interpolation code is available on request from the first author.

Unique-order interpolative coding for fast querying and space-efficient indexing in information retrieval systems

This paper presents a size reduction method for the inverted file, the most suitable indexing structure for an information retrieval system (IRS). We notice that in an inverted file the document identifiers for a given word are usually clustered. While this clustering property can be used in reducing the size of the inverted file, good compression as well as fast decompression must both be available. In this paper, we present a method that can facilitate coding and decoding processes for interpolative coding using recursion elimination and loop unwinding. We call this method the unique-order interpolative coding. It can calculate the lower and upper bounds of every document identifier for a binary code without using a recursive process, hence the decompression time can be greatly reduced. Moreover, it also can exploit document identifier clustering to compress the inverted file efficiently. Compared with the other well-known compression methods, our method provides fast decoding speed and excellent compression. This method can also be used to support a self-indexing strategy. Therefore our research work in this paper provides a feasible way to build a fast and space-economical IRS.

ヘリコプタのブレード/渦干渉騒音の解析

Two types of prediction tools for helicopter noise have been developed under the cooperative research between Advanced Technology Institute of Commuter Helicopter Ltd. (ATIC) and National Aerospace Laboratory (NAL) . One of them is a combined method of CAMRAD II, interpolation code for blade motion and wake geometry, aerodynamic code of 3D unsteady Euler solver, and aeroacoustic code based on Ffowcs Williams and Hawkings (FW-H) formulation. The other consists of CAMRAD II, 3D unsteady Euler solver using moving overlapped grid method, and FW-H code. The acoustic waveform of Blade-Vortex Interaction (BVI) noise predicted by the former tool is in good agreement with the experimental data of 1/7-scale model AH-1 Operational Loads Survey (OLS) rotor. This method is applied to investigate the effect of blade-tip shape on the intensity of BVI noise. As a result, it is shown that anhedral and swept-forward tip shapes effectively reduce the BVI noise of OLS rotor in a descent flight condition. The predicted Effective Perceived Noise Level (EPNL) of a helicopter is also compared with the experimental data obtained by ATIC and reasonable correlation is obtained. The latter tool successfully predicts the distinct spikes in the BVI wave-form of ATIC model rotor tested in German-Dutch Wind Tunnel (DNW) . In the comparison of measured and calculated carpet noise contours, reasonable agreement is obtained. The present tools are expected to be useful for the design of low-noise helicopters in the future.

Binary Interpolative Coding for Effective Index Compression

Information retrieval systems contain large volumes of text, and currently have typical sizes into the gigabyte range. Inverted indexes are one important method for providing search facilities into...

An interpolative subband coding algorithm for lossless image compression

Abstract This paper presents a new interpolative subband coding (ISC) algorithm for efficient lossless image compression. An investigation of the decorrelation performance of typical interpolation techniques is presented. A new representation of the subband data and a new context modelling scheme are proposed. Simulations have shown that the ISC algorithm results in an average bit-rate very close to that of the CALIC algorithm and almost the same as that of the S+P transform. The decorrelation part of the ISC is also simpler than that of the S+P transform. Thus, the proposed method provides an alternative way for efficient lossless image compression.

Reversible decorrelation method for progressive transmission of 3-D medical image.

In this paper, we present a new reversible decorrelation method of three-dimensional (3-D) medical images for progressive transmission. Progressive transmission of an image permits gradual improvement of image quality while being displayed. When the amount of image data is very large, as a 3-D medical image, the progressive transmission plays an important role in viewing or browsing the image. The data structure presented in this paper takes account of interframe correlation as well as intraframe correlation of the 3-D image. This type of data structure has been termed the 3-D hierarchy embedded differential image (3-D-HEDI) as was derived from the earlier HEDI structure. Experiments were conducted to verify the performance of 3-D HEDI in terms of the decorrelation efficiency as well as the progressive transmission efficiency. It is compared with those of conventional hierarchy interpolation (HINT), two-dimensional (2-D) HEDI and differential pulse code modulation (DPCM). Experimental results indicate that 3-D HEDI outperforms HINT, 2-D HEDI and DPCM in both decorrelation efficiency as well as the progressive transmission efficiency on 3-D medical images.

Pitch-controlled variable bitrate CELP speech coding

Most research in efficient speech coding concentrated for many years on algorithms which produced a fixed bit rate. Fixed bit rates are, however, not a requirement for modern packet-based telecommunications and computer networks as well as voice storage applications. This makes the implementation of speech coders feasible, which adapt to the changing properties of speech for improved efficiency or quality. Variable bit-rate coding has therefore become the focus of considerable research activity in recent years [A. Gersho and E. Paksoy, ‘‘Variable Bit Rate Coding,’’ Signal Processing VII, Theories and Applications, EUSIPCO 1994, pp. 1169–1173; L. Zhang et al., ‘‘A CELP Variable Rate Speech Codec with Low Average Rate,’’ ICASSP 1997, pp. 735–738; B. C. Xydeas, ‘‘Source Driven Variable Bit Rate Prototype Interpolation Coding,’’ ICASSP 1996, p. 220; B. Shen et al., ‘‘A Robust Variable-Rate Speech Coder,’’ ICASSP 1995, p. 249]. While all of these coders focus on classification procedures for efficient bit allocation, the analysis frame size remains mainly static. The coder featured in this paper adapts the analysis frame size and bit allocation according to the pitch of the signal. A pitch frame extractor and classifier at the front end feeds the detected frame into the speech coding back end, which uses traditional CELP-based techniques [B. S. Schroeder et al., ‘‘CodeExcited Linear Prediction (CELP): High Quality Speech at Very Low Bit Rates,’’ ICASSP 1985, pp. 937–940]. This approach allows the reduction of the bit rate from a constant 4800 bps (bits per second) with original CELP to typically 3200–4000 bps, depending on the speech situation. This figure is even reduced to typically 2600–3200 with the inclusion of Voice Activity Detection. The speech quality equals the quality of the original CELP coder.

Hybrid adaptive block truncation coding for image compression

A hybrid adaptive block truncation coding (HABTC) method is presented to improve block truncation coding (BTC)-related compression methods for gray-level images. The basic idea behind the method is to use various coding schemes to take advantage of local image charac- teristics. A simple linear interpolation coding scheme and a very basic predictive coding scheme are used to improve the compression ratio of the homogeneous area of the image. Moreover, a four-level BTC, whose thresholds are obtained using a radius-weighted mean (RWM), is ap- plied to encode the inhomogeneous area. The bits per pixel/peak SNR (bpp/PSNR) values listed in many other BTC-related papers are cited and compared with ours. It is found that reasonable compression ratio is obtained by the proposed HABTC method and the visual quality of the decoded images is also acceptable. © 1997 Society of Photo-Optical Instrumen- tation Engineers. (S0091-3286(97)00104-9) Subject terms: image compression; hybrid adaptive block truncation coding; lin- ear interpolation coding; predictive coding; radius weighted mean; vector quanti- zation.

A Novel Analysis by Synthesis Approach to Prototoype Interpolation Speech Coding Based on Discrete Cosine Transform (AbS/DCT-PIC)

This paper proposes a novel Analysis by Synthesis approach to the Discrete Cosine Transform based Prototype Interpolation Coding (AbS/DCT-PIC) system that describes a second prototype for every voiced frame, which keeps the dynamics of the pitch cycles based on minimising a mean square error (MSE) criterion. This approach optimises a second set of DCT coefficients and therefore performs better than single value representation of the signal to change ratio (SCR) which prototype waveform interpolation coders employ. In addition, the proposed system delivers excellent speech quality at or above 3.6 Kb/s and is robust to pitch estimation errors.

OPAL Equation-of-State Tables for Astrophysical Applications

OPAL opacities have recently helped to resolve a number of long-standing discrepancies between theory and observation. This success has made it important to provide the associated equation-of-state (EOS) data. The OPAL EOS is based on an activity expansion of the grand canonical partition function of the plasma in terms of its fundamental constituents (electrons and nuclei). The formation of composite particles and many-body effects on the internal bound states occur naturally in this approach. Hence, pressure ionization is a consequence of the theory. In contrast, commonly used approaches, all of which are based on minimization of free energy, are forced to assert the effect of the plasma on composite particles and must rely on an ad hoc treatment of pressure ionization. Another advantage of the OPAL approach is that it provides a systematic expansion in the Coulomb coupling parameter that includes subtle quantum effects generally not considered in other EOS calculations. Tables have been generated that provide pressure, internal energy, entropy, and a variety of derivative quantities. These tables cover a fairly broad range of conditions and compositions applicable to general stellar-evolution calculations for stars more massive than {approximately}0.8 {ital M}{sub {circle_dot}}. An interpolation code is provided along with themore » tables to facilitate their use. {copyright} {ital 1996 The American Astronomical Society.}« less

Effiziente sehr niederratige Sprachübertragung mittels Interblock-Codierung

The article presents a new data compression scheme for very-low-rate speech coding at 1000 b/s and below. The method which is called matrix product quantization (MPQ) encodes matrices containing successive LPC parameter vectors by a product formulation of two matrices which describe the average parameter vector and the temporal parameter contour. MPQ can be applied in fixed rate as well as in variable rate coding systems. At a fixed bit rate MPQ yields a very high coding efficiency at relatively low coding delay and medium complexity. Applied in a variable rate segment vocoder MPQ achieves even higher compression gains at the cost of increased coding delay and complexity. In general, it is shown that interblock coding, which is made by MPQ, considerably outperforms memoryless coding. In a particular comparison to interpolative coding methods which is often used for very-low-rate speech coding, MPQ is clearly superior since only MPQ is able to exactly model the temporal parameter contour.

Interpolative three-level block truncation coding algorithm

Zeng (see ibid., vol.27, p.1126-8, 1991) has described an interpolative two-level block truncation coding (BTC) image compression algorithm. The authors extend the work of Zeng to a three-level interpolative BTC algorithm. Compared to Zeng, the new algorithm gives reconstructed images with substantially higher image quality with no increase in bit rate.

A two-dimensional nonuniform sampling expansion model

Assuming a previously established model for one-dimensional (1-D) signal interpolation, this paper presents the extension of the above results for finite two-dimensional (2-D) signals. The proposed method consists of a cascade having three stages: (i) 2-D nonuniform sampling according to Chebyshev polynomial roots; (ii) 2-D Discrete Cosine Transform (DCT) applied on the matrix of nonuniformly spaced samples; (iii) 2-D interpolation using the matrix of DCT coefficients deduced at stage (ii). We have proved that the set of Chebyshev nonuniformly taken 2-D signal samples and the coefficients of the corresponding 2-D Chebyshev polynomial finite series are essentially a 2-D DCT pair. It provides a method to a fast computation of the coefficients of an optimum 2-D interpolation formula. By assuming the 2-D signal is band-limited and has finite energy, we have deduced an upper bound for the magnitude of the sampling reconstruction error and the corresponding sufficient conditions of convergence for interpolation. We have also evaluated the application of our model for data compression, pointing out the advantage of the proposed interpolative coding (based on 2-D nonuniform sampling and 2-D DCT) over the corresponding classical method (based on 2-D uniform sampling and 2-D DCT). Some numerical examples are given.

Variable-Rate Block Interpolative Coding for Satellite Images

While many image compression schemes have come up in recent years, a new scheme using two-dimensional interpolation for satellite images is presented in this paper. This scheme is very useful for onboard application since it achieves reasonable compression with very simple encoding and decoding operation. Also the scheme, namely Block Interpolative Coding, has the facility for fixing the required compression, quality and distortion. Simulation results on Indian remote sensing satellite images have been presented.

Predictive image coding using multiresolution multiplicative autoregressive models

The authors present a new image coding technique called multiresolution multiplicative autoregressive coding. It is a hybrid method that integrates multiresolution interpolative coding and two-dimensional predictive coding based on multiplicative autoregressive models. In addition, the proposed scheme utilises newly developed methods for block adaptive quantisation of prediction errors and fixed-to-variable-length block coding. The performance of the proposed scheme is tested on three different images and, in all cases, reconstructed images of reasonably good quality are obtained at bit rates less than 0.35 bits per pixel. The bit rates and the signal-to-noise-ratios of the reconstructed images compare favourably with the existing low bit rate image coding methods.

Optical oversampled analog-to-digital conversion

A new approach to optical analog-to-digital (A/D) conversion based on oversampling and interpolative coding techniques is described, and both interferometric and noninterferometric architectures based on this method are presented. This new approach combines the high resolution of classical oversampled A/D conversion with the high speed of optical processing technology to extend the resolution and conversion rates beyond that currently possible with other electronic or optical converters. The proposed optical converters are simple, consisting of multiple quantum well self-electro-optic effect devices, photodetectors, and common optical components that are capable of operating at sampling rates of up to 15 Gbits/s and that can provide scalable resolutions of 16 and 8 bits at a conversion rate of 117 and 938 MHz, respectively.

Comments on "Interpolative multiresolution coding of advanced television with compatible subchannels" (and reply and additional comments)

Recently, Uz et al. (ibid., vol.1., no.1, p.86-99, 1991) analyzed the propagation of quantization noise in a pyramid (with feedback) and subband decomposition schemes. In this study each band was independently quantized by a scalar quantizer of equal step size. The resulting reconstruction error spectrum indicated that in both the pyramid (without feedback) and subband coding schemes, noise was building up in lower frequencies. The commenters show that a quantizer assignment method, using mean-square-error (MSE) optimal bit allocation, avoids the problem. The authors argue that the problem is more involved than just MSE optimal bit allocation, and that compatible coding was the focus, as well as guaranteed quality, effects of numerical computations, and perceptual effects. The commenters further support their argument. >

Performance analysis of reversible image compression techniques for high-resolution digital teleradiology

The performances of a number of block-based, reversible, compression algorithms suitable for compression of very-large-format images (4096x4096 pixels or more) are compared to that of a novel two-dimensional linear predictive coder developed by extending the multichannel version of the Burg algorithm to two dimensions. The compression schemes implemented are: Huffman coding, Lempel-Ziv coding, arithmetic coding, two-dimensional linear predictive coding (in addition to the aforementioned one), transform coding using discrete Fourier-, discrete cosine-, and discrete Walsh transforms, linear interpolative coding, and combinations thereof. The performances of these coding techniques for a few mammograms and chest radiographs digitized to sizes up to 4096x4096 10 b pixels are discussed. Compression from 10 b to 2.5-3.0 b/pixel on these images has been achieved without any loss of information. The modified multichannel linear predictor outperforms the other methods while offering certain advantages in implementation.