Image analysis based on two dimensional Hilbert Huang Transform
Lihong Qiao, Sisi Chen
Abstract
Lihong Qiao, Sisi Chen
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.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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