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The superdirective beamformer, while attractive for processing broadband acoustic signals, often suffers from the problem of white noise amplification. So, its application requires well-designed acoustic arrays with sensors of extremely low self-noise level, which is difficult if not impossible to attain. In this paper, a new binaural superdirective beamformer is proposed, which is divided into two sub-beamformers. Based on studies and facts in psychoacoustics, these two filters are designed in such a way that they are orthogonal to each other to make the white noise components in the binaural beamforming outputs incoherent while maximizing the output interaural coherence of the diffuse noise, which is important for the brain to localize the sound source of interest. As a result, the signal of interest in the binaural superdirective beamformer’s outputs is in phase but the white noise components in the outputs are random phase, so the human auditory system can better separate the acoustic signal of interest from white noise by listening to the outputs of the proposed approach. Experimental results show that the derived binaural superdirective beamformer is superior to its conventional monaural counterpart.

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While differential beamformers have been widely used in voice communication and human-machine speech interface systems to enhance speech signals of interest, how to design such beamformers that on the one hand can achieve the highest possible directivity factor (DF) and on the other hand are able to obtain a certain level of white noise gain (WNG), so that they are robust enough to sensors' self noise and array imperfections is still a challenging issue. This paper studies the problem of robust differential beamforming with small-size arrays to achieve a high DF. It presents a method for the design of differential beamformers with uniform linear arrays. We first generate differential pressure signals by applying the recently developed forward spatial difference operator to the outputs of the array with pressure sensors. The pressure microphone observation signals and the differential pressure signals are then put together, and a combined beamformer is subsequently designed, which consists of two sub-beamformers, one operates on the pressure microphone observations and the other on the differential pressure signals. A new class of combined differential beamformers are introduced, which can achieve different levels of compromises between DF and WNG using an adjustable parameter.

The nonuniform emissivity of material surface will adversely affect the detection results of the thermal imaging technology. Aiming at the influence of uneven emissivity on the dynamic detection mode of eddy current thermography, a suppression method based on edge detection is proposed in this paper. Since the traditional threshold selection methods are not ideal, a local adaptive threshold selection (LATS) method is applied in this study. This method can automatically obtain the optimal threshold for edge detection to suppress the influence of uneven emissivity. Roberts, Sobel, Prewitt, and Canny operators are tested by using LATS. The results show that Roberts, Sobel, and Prewitt operators can achieve the suppression effect, but the effect of Sobel and Prewitt are similar and better than Roberts.