Adaptive Impulse Detection Based Approaches for the Noise Reduction in Heart Image Sequences

This paper focuses on three-dimensional (3-D) adaptive median filters based on the impulse detection approach designed to effectively remove the impulse noise from cardiographic image sequences. Impulse noise affects the useful information in the form of bit errors and it introduces to the image high frequency changes that prohibit to process and to evaluate the heart dynamics correctly. Therefore biomedical imaging such as vascular imaging and quantification of heart dynamics is closely related to digital filtering. In order to suppress impulse noise effectively, well-known non-linear filters based on the robust order-statistic theory provide interesting results. Although median filters have excellent impulse noise attenuation characteristics, their performance is often accompanied by undesired processing of noise-free samples resulting in edge blurring. The reason is that median filters do not satisfy the superposition property and thus the optimal filtering situation where only noisy samples are affected can never be fully obtained. The presented adaptive impulse detection based median filters, can achieve the excellent balance between the noise suppression and the signal-detail preservation. In this paper, the performance of the proposed approaches is successfully tested for the heart image sequence of 38 frames and the wide range of noise corruption intensity. The results are evaluated in terms of mean absolute error, mean square error and cross correlation.