2012Unpublished venueRequires access

Image analysis based on two dimensional Hilbert Huang Transform

Lihong Qiao, Sisi Chen

Open publisher page 2 citations

Abstract

Hilbert Huang Transform is a new developed method especially suitable for non-stationary signal processing. In this paper, we propose a two dimensional Hilbert-Huang Transform based on Bidimensional Empirical Mode Decomposition (BEMD) and Bi-orthant analytic signal. Bidimensional Empirical Mode Decomposition is adaptive signal decomposition method and its decomposition results are almost monocomponent. Bi-orthant analytic signal satisfies most of the two dimensional extension properties and is especially suitable for the monocomponent. In detail, the image is first decomposed to several comoponents by Bidimensional Empirical Mode Decomposition. Then we get the two dimensional Bi-orthant analytic signal. Two dimensional Hilbert spectral characters are got based on BEMD and two dimensional Bi-orthant analytic signals. Then we use this method in image analysis, and got the instantaneous amplitude, the instantaneous phase, and the instantaneous frequencies. We illustrate the techniques on natural images, and demonstrate the estimated instantaneous frequencies using the needle program. These features inflect the intrinsic characters of image.

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What this paper is about

Hilbert Huang Transform is a new developed method especially suitable for non-stationary signal processing. In this paper, we propose a two dimensional Hilbert-Huang Transform based on Bidimensional Empirical Mode Decomposition (BEMD) and Bi-orthant analytic signal. Bidimensional Empirical Mode Decomposition is adaptive signal decomposition method and its decomposition results are almost monocomponent. Bi-orthant analytic signal satisfies most of the two dimensional extension properties and is especially suitable for the monocomponent. In detail, the image is first decomposed to several comoponents by Bidimensional Empirical Mode Decomposition. Then we get the two dimensional Bi-orthant analytic signal. Two dimensional Hilbert spectral characters are got based on BEMD and two dimensional Bi-orthant analytic signals. Then we use this method in image analysis, and got the instantaneous amplitude, the instantaneous phase, and the instantaneous frequencies. We illustrate the techniques on natural images, and demonstrate the estimated instantaneous frequencies using the needle program. These features inflect the intrinsic characters of image.

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Available abstract

Hilbert Huang Transform is a new developed method especially suitable for non-stationary signal processing. In this paper, we propose a two dimensional Hilbert-Huang Transform based on Bidimensional Empirical Mode Decomposition (BEMD) and Bi-orthant analytic signal. Bidimensional Empirical Mode Decomposition is adaptive signal decomposition method and its decomposition results are almost monocomponent. Bi-orthant analytic signal satisfies most of the two dimensional extension properties and is especially suitable for the monocomponent. In detail, the image is first decomposed to several comoponents by Bidimensional Empirical Mode Decomposition. Then we get the two dimensional Bi-orthant analytic signal. Two dimensional Hilbert spectral characters are got based on BEMD and two dimensional Bi-orthant analytic signals. Then we use this method in image analysis, and got the instantaneous amplitude, the instantaneous phase, and the instantaneous frequencies. We illustrate the techniques on natural images, and demonstrate the estimated instantaneous frequencies using the needle program. These features inflect the intrinsic characters of image.

Key concepts: Hilbert–Huang transform, Orthant, Hilbert transform, Instantaneous phase, Analytic signal, Hilbert spectral analysis, Mathematics, Signal processing

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