Recursive estimation of two-dimensional processes with application to image processing

Lashgari, B.; Silverman, L.

doi:10.1007/bf01600057

Cited by 6 publications

(1 citation statement)

References 19 publications

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“…Two‐dimensional finite impulse response (2D‐FIR) digital filter plays a vital role in figuring out a variety of problems in the field of biomedical signal processing, image processing, speech processing, communication systems, control system and data processing [1–8]. These applications include biomedical signal detection [8], beamforming in cognitive radio systems [9], seismic multiple removal [10], iris recognition [11], image denoising [12], are to name a few. A wide range of applications of the 2D‐FIR filter, encourages more and more the practitioners to develop a high performance 2D‐FIR filter in the past few decades.…”

Section: Introductionmentioning

confidence: 99%

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method

Aggarwal¹,

Kumar²,

Rawat

2019

IET signal process.

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The mathematical formulation of the two‐dimensional (2D) L1 ‐method for designing of the 2D‐finite impulse response (FIR) filter is introduced in this study. It features the 2D‐FIR filter with narrow transition width and flatter passband and stopband response. The 2D complexity is reduced using the quadrant symmetricity concept for the reduction of filter coefficients to be evaluated. Here, the unique features of the 2D L1 ‐method are exploited for the efficient design of the 2D‐FIR filter. To study the effectiveness of the 2D‐FIR filter using the proposed method, its performance is compared with other existing 2D‐FIR filter methods. Simulation results for five design example of 2D lowpass, highpass, bandpass, bandstop filters and 2D differentiator are presented to prove the efficacy of the proposed design in terms of passband ripple, stopband ripple, passband error, stopband error and magnitude response.

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Section: Introductionmentioning

confidence: 99%

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method

Aggarwal¹,

Kumar²,

Rawat

2019

IET signal process.

View full text Add to dashboard Cite

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Optimal Design of 2D FIR Filters with Quadrantally Symmetric Properties Using Fractional Derivative Constraints

Aggarwal

Kumar

Rawat

et al. 2016

Circuits Syst Signal Process

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Image modeling based on a 2-D stochastic subspace system identification algorithm

Ramos

Mercère

2016

Multidim Syst Sign Process

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Fitting a causal dynamic model to an image is a fundamental problem in image processing, pattern recognition, and computer vision. In image restoration, for instance, the goal is to recover an estimate of the true image, preferably in the form of a parametric model, given an image that has been degraded by a combination of blur and additive white Gaussian noise. In texture analysis, on the other hand, a model of a particular texture image can serve as a tool for simulating texture patterns. Finally, in image enhancement one computes a model of the true image and the residuals between the image and the modeled image can be interpreted as the result of applying a de-noising filter. There are numerous other applications within the field of image processing that require a causal dynamic model. Such is the case in scene analysis, machined parts inspection, and biometric analysis, to name only a few. There are many types of causal dynamic models that have been proposed in the literature, among which the autoregressive moving average and state-space models (i.e., Kalman filter) are the most commonly used. In this paper we introduce a 2-D stochastic state-space system identification algorithm for fitting a quarter plane causal dynamic Roesser model to an image. The algorithm constructs a causal, recursive, and separable-in-denominator 2-D Kalman filter model. The algorithm is tested with three real images and the quality of the estimated images are assessed.

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Recursive estimation of two-dimensional processes with application to image processing

Cited by 6 publications

References 19 publications

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method

Optimal Design of 2D FIR Filters with Quadrantally Symmetric Properties Using Fractional Derivative Constraints

Image modeling based on a 2-D stochastic subspace system identification algorithm

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Recursive estimation of two-dimensional processes with application to image processing

Cited by 6 publications

References 19 publications

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL1‐method

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL1‐method

Optimal Design of 2D FIR Filters with Quadrantally Symmetric Properties Using Fractional Derivative Constraints

Image modeling based on a 2-D stochastic subspace system identification algorithm

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Product

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Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method

Design of two‐dimensional FIR filters with quadrantally symmetric properties using the 2DL₁‐method