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76
Survey: Interpolation Methods in Medical Image Processing
 IEEE Transactions on Medical Imaging
, 1999
"... Abstract — Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation ker ..."
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Cited by 155 (2 self)
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Abstract — Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sinc; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic Bspline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1 2 1upto 8 2 8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced
A chronology of interpolation: From ancient astronomy to modern signal and image processing
 Proceedings of the IEEE
, 2002
"... This paper presents a chronological overview of the developments in interpolation theory, from the earliest times to the present date. It brings out the connections between the results obtained in different ages, thereby putting the techniques currently used in signal and image processing into histo ..."
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Cited by 102 (0 self)
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This paper presents a chronological overview of the developments in interpolation theory, from the earliest times to the present date. It brings out the connections between the results obtained in different ages, thereby putting the techniques currently used in signal and image processing into historical perspective. A summary of the insights and recommendations that follow from relatively recent theoretical as well as experimental studies concludes the presentation. Keywords—Approximation, convolutionbased interpolation, history, image processing, polynomial interpolation, signal processing, splines. “It is an extremely useful thing to have knowledge of the true origins of memorable discoveries, especially those that have been found not by accident but by dint of meditation. It is not so much that thereby history may attribute to each man his own discoveries and others should be encouraged to earn like commendation, as that the art of making discoveries should be extended by considering noteworthy examples of it. ” 1 I.
MOMS: MaximalOrder Interpolation of Minimal Support
 IEEE Trans. Image Process
, 2001
"... We consider the problem of interpolating a signal using a linear combination of shifted versions of a compactlysupported basis function ( ). We first give the expression of the 's that have minimal support for a given accuracy (also known as "approximation order"). This class of func ..."
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Cited by 74 (28 self)
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We consider the problem of interpolating a signal using a linear combination of shifted versions of a compactlysupported basis function ( ). We first give the expression of the 's that have minimal support for a given accuracy (also known as "approximation order"). This class of functions, which we call maximal orderminimalsupport functions (MOMS) is made of linear combinations of the Bspline of same order and of its derivatives.
Quadratic Interpolation for Image Resampling
, 1997
"... Nearestneighbour, linear, and various cubic interpolation functions are frequently used in image resampling. Quadratic functions have been disregarded, largely because they have been thought to introduce phase distortions. This is shown not to be the case, and a family of quadratic functions is der ..."
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Cited by 44 (4 self)
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Nearestneighbour, linear, and various cubic interpolation functions are frequently used in image resampling. Quadratic functions have been disregarded, largely because they have been thought to introduce phase distortions. This is shown not to be the case, and a family of quadratic functions is derived. The interpolating member of this family has visual quality close to that of the CatmullRom cubic, yet requires only sixty percent of the computation time.
Generalized Stochastic Subdivision
 ACM Transactions on Graphics
, 1987
"... This paper describes the basis for techniques such as stochastic subdivision in the theory of random processes and estimation theory. The popular stochastic subdivision construction is then generalized to provide control of the autocorrelation and spectral properties of the synthesized random functi ..."
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Cited by 42 (3 self)
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This paper describes the basis for techniques such as stochastic subdivision in the theory of random processes and estimation theory. The popular stochastic subdivision construction is then generalized to provide control of the autocorrelation and spectral properties of the synthesized random functions. The generalized construction is suitable for generating a variety of perceptually distinct highquality random functions, including those with nonfractal spectra and directional or oscillatory characteristics. It is argued that a spectral modeling approach provides a more powerful and somewhat more intuitive perceptual characterization of random processes than does the fractal model. Synthetic textures and terrains are presented as a means of visually evaluating the generalized subdivision technique. Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation; I.3.7 [Computer Graphics]: Three Dimensional Graphics and Realism <F11.
A timeefficient and accurate strain estimation concept for ultrasonic elastography using iterative phase zero estimation,“ submitted to
 IEEE Trans. Ultrason., Ferroelect., Freq. Control
"... Abstract—In ultrasonic elastography, the exact estimation of temporal displacements between two signals is the key to estimate strain. An algorithm was previously proposed that estimates these displacements using phase differences of the corresponding baseband signals. A major advantage of these ..."
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Cited by 41 (3 self)
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Abstract—In ultrasonic elastography, the exact estimation of temporal displacements between two signals is the key to estimate strain. An algorithm was previously proposed that estimates these displacements using phase differences of the corresponding baseband signals. A major advantage of these algorithms compared with correlation techniques is its computational efficiency. In this paper, an extension of the algorithm is presented that iteratively takes into account the time shifts of the signals to overcome the problems of aliasing and accuracy in the estimation of the phase shift. Thus, it can be proven that the algorithm is equivalent to the search of the maximum of the correlation function. Furthermore, a robust logarithmic compression is proposed that only compresses the envelope of the signal. This compression does not introduce systematic errors and significantly reduces decorrelation noise. The resulting algorithm is a computationally simple and very fast alternative to conventional correlation techniques, and accuracy of strain images is improved. I.
The Digital FrontEnd of Software Radio Terminals
 IEEE Personal Communications
, 1999
"... When expanding digital signal processing of mobile communications terminals toward the antenna while making the terminal more wideband in order to be able to cope with different mobile communications standards in a softwareradiobased terminal, the designer is faced with strong requirements such ..."
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Cited by 33 (4 self)
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When expanding digital signal processing of mobile communications terminals toward the antenna while making the terminal more wideband in order to be able to cope with different mobile communications standards in a softwareradiobased terminal, the designer is faced with strong requirements such as bandwidth and dynamic range. Many publications claim that only reconfigurable hardware such as FPGAs can simultaneously cope with such diversity and requirements. Starting with considerations of the receiver architecture, we describe key functionalities of the digital frontend and highlight how signal characteristics of mobile communications signals and commonalities among different signal processing operations can be exploited to great advantage, eventually enabling implementations on an ASIC that, although not reconfigurable, would empower the software radio concept.
Sample Rate Conversion for Software Radio
, 2000
"... Software radio terminals must be able to process different communications standards which are generally based on different master clock rates and thus employ different bit/chiprates. A straightforward solution to cope with this diversity of master clock rates in one terminal is to employ dedicated ..."
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Cited by 24 (3 self)
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Software radio terminals must be able to process different communications standards which are generally based on different master clock rates and thus employ different bit/chiprates. A straightforward solution to cope with this diversity of master clock rates in one terminal is to employ dedicated master clocks for each standard of operation. Being too costly in most cases, this kind of solution moreover limits the applicability of a once realized and thus fixed terminal. The smart solution to this problem is to run the terminal on a fixed clock rate, and to perform digital sample rate conversion that can be controlled by software and thus, empowers the software radio concept.
Image Resampling
, 1992
"... This dissertation considers several aspects of the process ..."
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Cited by 21 (4 self)
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This dissertation considers several aspects of the process
A Method for Extrapolation of Missing Digital Audio Data
 J. Audio Eng. Soc
, 1994
"... Thispreprinthas beenreproducedfromthe author'sadvance manuscript,withoutediting,correctionsorconsiderationby the ReviewBoard. TheAES takesno responsibilityfor the contents. Additionalpreprintsmaybe obtainedby sendingrequestand remittanceto theAudioEngineeringSociety,60 East42nd St., ..."
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Cited by 15 (1 self)
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Thispreprinthas beenreproducedfromthe author'sadvance manuscript,withoutediting,correctionsorconsiderationby the ReviewBoard. TheAES takesno responsibilityfor the contents. Additionalpreprintsmaybe obtainedby sendingrequestand remittanceto theAudioEngineeringSociety,60 East42nd St.,