Noise cancellation in IR video based on Empirical Mode Decomposition

Currently there is a huge demand for simple low cost IR cameras for both civil and military applications, among which one of the most common is the surveillance of restricted access zones. In the design of low cost IR cameras, it is necessary to avoid the use of several elements present in more sophisticated cameras, such as the refrigeration systems and the temperature control of the detectors, so as to prevent the use of a mechanical modulator of the incident radiation (chopper). Consequently, the detection algorithms must reliably separate the target signal from high noise and drift caused by temporal variations of the background image of the scene and the additional drift due to thermal instability detectors. A very important step towards this goal is the design of a preprocessing stage to eliminate noise. Thus, in this work we propose using the Empirical Mode Decomposition (EMD) method to attain this objective. In order to evaluate the quality of the reconstructed clean signal, the Average to Peak Ratio is assessed to evaluate the effectiveness in reconstructing the waveform of the signal from the target. We compare the EMD method with other classical method of noise cancellation based on the Discrete Wavelet Transform (DWT). The results reported by simulations show that the proposed scheme based on EMD performs better than traditional ones.