A new 2-D LMS adaptive algorithm

Ohki, Makoto; Hashiguchi, Sumihisa

doi:10.1109/icassp.1991.150823

Cited by 6 publications

(4 citation statements)

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“…The minimization process leads to finding the set of three reflection coefficients such that when applied in (11), the output, , is a minimum. (11) can be reformulated into a weighted least squares set of equations as described by (12) where (13) diag (14) and (15) Equation 12is repeated for each output:…”

Section: A Development Of a Single 2-d Al Lattice Stagementioning

confidence: 99%

“…The goal here, however, is to compare 2-D AL with the algorithm used in [16], which used the raster scan method. There are also other 2-D methods to update the weights as proposed by Okhi et al [14].…”

Section: A 2-d Lms Algorithm Descriptionmentioning

confidence: 99%

“…This is different than the gradient approach proposed by Youlal et al [11], who used the same basic structure of [1] for joint process estimation. In this paper, the correlations used to calculate the reflection coefficients are updated in a 2-D method similar to the approach that was used in [14] for a 2-D adaptive LMS filter. This update scheme removes the dependence of the algorithm on the scanning method or direction, since the updates for the correlation values use both past horizontal and past vertical components at each new pixel.…”

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confidence: 99%

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Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm

Ffrench¹,

Zeidler

1997

IEEE Trans. on Image Process.

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Two-dimensional (2-D) adaptive filtering is a technique that can be applied to many image processing applications. This paper will focus on the development of an improved 2-D adaptive lattice algorithm (2-D AL) and its application to the removal of correlated clutter to enhance the detectability of small objects in images. The two improvements proposed here are increased flexibility in the calculation of the reflection coefficients and a 2-D method to update the correlations used in the 2-D AL algorithm. The 2-D AL algorithm is shown to predict correlated clutter in image data and the resulting filter is compared with an ideal Wiener-Hopf filter. The results of the clutter removal will be compared to previously published ones for a 2-D least mean square (LMS) algorithm. 2-D AL is better able to predict spatially varying clutter than the 2-D LMS algorithm, since it converges faster to new image properties. Examples of these improvements are shown for a spatially varying 2-D sinusoid in white noise and simulated clouds. The 2-D LMS and 2-D AL algorithms are also shown to enhance a mammogram image for the detection of small microcalcifications and stellate lesions.

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Section: A Development Of a Single 2-d Al Lattice Stagementioning

confidence: 99%

Section: A 2-d Lms Algorithm Descriptionmentioning

confidence: 99%

mentioning

confidence: 99%

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Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm

Ffrench¹,

Zeidler

1997

IEEE Trans. on Image Process.

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“…x + (y?y 0 ) 2 2 y (21) where ? is the maximum value of the object intensity function, (x 0 ; y 0 ) is the position of the center of the object, and ( x ; y ) de ne the spatial spread of the object.…”

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confidence: 99%

Performance evaluation of 2-D adaptive prediction filters for detection of small objects in image data

Soni

Zeidler

1993

IEEE Trans. on Image Process.

159

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This work studies the performance of dimensional least mean square (TDLMS) adaptive filters as prewhitening filters for the detection of small objects in image data. The object of interest is assumed to have a very small spatial spread and is obscured by correlated clutter of much larger spatial extent. The correlated clutter is predicted and subtracted from the input signal, leaving components of the spatially small signal in the residual output. The receiver operating characteristics of a detection system augmented by a TDLMS prewhitening filter are plotted using Monte-Carlo techniques. It is shown that such a detector has better operating characteristics than a conventional matched filter in the presence of correlated clutter. For very low signal-to-background ratios, TDLMS-based detection systems show a considerable reduction in the number of false alarms. The output energy in both the residual and prediction channels of such filters is shown to be dependent on the correlation length of the various components in the input signal. False alarm reduction and detection gains obtained by using this detection scheme on thermal infrared sensor data with known object positions is presented.

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Image registration based on a novel 2-D adaptive filter algorithm

Fan

et al. 2012

2012 12th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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A new 2-D LMS adaptive algorithm

Cited by 6 publications

References 4 publications

Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm

Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm

Performance evaluation of 2-D adaptive prediction filters for detection of small objects in image data

Image registration based on a novel 2-D adaptive filter algorithm

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