Efficient denoising approach based eulerian video magnification for colour and motion variations

Abstract

Digital video magnification is a computer-based microscope, which is useful to detect subtle changes to human eyes in recorded videos. This technology can be employed in several areas such as medical, biological, mechanical and physical applications. Eulerian is the most popular approach in video magnification. However, amplifying the subtle changes in video produces amplifying the subtle noise. This paper proposes an approach to reduce amplified noise in magnified video for both type of changes amplifications, color and motion. The proposed approach processes the resulted video from Eulerian algorithm whether linear or phase based in order to noise cancellation. The approach utilizes wavelet denoising method to localize the frequencies of distributed noise over the different frequency bands. Subsequently, the energy of the coefficients under localized frequencies are attenuated by attenuating the amplitude of these coefficients. The experimental results of the proposed approach show its superiority over conventional linear and phase based Eulerian video magnification approaches in terms of quality of the resulted magnified videos. This allows to amplify the videos by larger amplification factor, so that several new applications can be added to the list of Eulerian video magnification users. Furthermore, the processing time does not significantly increase, the increment is only less than 3% of the overall processing compare to conventional Eulerian video magnification.