Image Denoising Based on Structural BIMF

Abstract

Image denoising is an important process for image analysis. It is always a pre-processing step before feeding its result to the next process. Although many papers based on statistical filter are presented for noise reduction, those still need to improve the quality of image. Bidimensional empirical mode decomposition (BEMD) is an adaptive image analysis method without a prior function for non-linear and non-stationary images in many applications. One of them is image denoising. The BEMD method can reduce the information loss by separating the noised and fundamental components into different bidimensional intrinsic mode function (BIMF) components. This makes it to be effective and flexible method. Therefore, this paper proposes image denoising based on structural BIMF. The proposed method not only removes the noise from noised image but also retrieves the main structure from noised image. Based on 44 noised images, the experimental results demonstrate that the performance of the proposed method outperforms that of baseline methods in terms of image quality assessments: PSNR, Qi, and TAA.