Abstract
In this paper, we propose a video-zoom driven audio-zoom algorithm in order to provide audio zooming effects in accordance with the degree of video-zoom. The proposed algorithm is designed based on a super-directive beamformer operating with a 4-channel microphone system, in conjunction with a soft masking process that considers the phase differences between microphones. Thus, the audio-zoom processed signal is obtained by multiplying an audio gain derived from a video-zoom level by the masked signal. After all, a real-time audio-zoom system is implemented on an ARM-CORETEX-A8 having a clock speed of 600 MHz after different levels of optimization are performed such as algorithmic level, C-code, and memory optimizations. To evaluate the complexity of the proposed real-time audio-zoom system, test data whose length is 21.3 seconds long is sampled at 48 kHz. As a result, it is shown from the experiments that the processing time for the proposed audio-zoom system occupies 14.6% or less of the ARM clock cycles. It is also shown from the experimental results performed in a semi-anechoic chamber that the signal with the front direction can be amplified by approximately 10 dB compared to the other directions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Matsumoto, M., Naono, H., Saitoh, H., Fujimura, K., Yasuno, Y.: Stereo zoom microphone for consumer video cameras. IEEE Transactions on Consumer Electronic 35(4), 759–766 (1989)
Brandstein, M., Ward, D.: Microphone Arrays. Springer, New York (2001)
Kates, J.M.: Super directive arrays for hearing aids. J. Acoust. Soc. Am. 94(4), 1930–1933 (1993)
Alik, M., Okamoto, M., Aoki, S., Matsui, H., Sakurai, T., Kaneda, Y.: Sound source segregation based on estimating incident angle of each frequency component of input signals acquired by multiple microphones. Acoustical Science and Technology 22(2), 149–157 (2001)
Wang, D.L., Brown, G.J.: Computational Auditory Scene Analysis: Algorithms and Applications. IEEE Press, Wiley-Interscience (2006)
Jeong, S.Y., Jeong, J.H., Oh, K.C.: Dominant speech enhancement based on SNR-adaptive soft mask filtering. In: Proceedings of ICASSP, pp. 1317–1320 (2009)
Hansen, C.H.: Noise control: from concept to application. Taylor & Francis, Inc., Abington (June 2005)
Chaili, M., Raghotham, D., Dominic, P.: Smooth PCM clipping for audio. In: Proceedings of AES 34th International Conference, pp. 1–4 (2008)
ARM Limited.: ARM1176JZF-S Technical Reference Manual (2006)
Texas Instruments: TMS320C6000 CPU and Instruction Set Reference Guide (2000)
Oppenheim, A.V., Schafer, R.W., Buck, J.R.: Discrete-time Signal Processing, 2nd edn. Prentice-Hall, Englewood Cliffs (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Park, N.I., Kim, S.M., Kim, H.K., Kim, J.W., Kim, M.B., Yun, S.W. (2010). Design and Implementation of a Video-Zoom Driven Digital Audio-Zoom System for Portable Digital Imaging Devices. In: Kim, Th., Pal, S.K., Grosky, W.I., Pissinou, N., Shih, T.K., Ślęzak, D. (eds) Signal Processing and Multimedia. MulGraB SIP 2010 2010. Communications in Computer and Information Science, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17641-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-17641-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17640-1
Online ISBN: 978-3-642-17641-8
eBook Packages: Computer ScienceComputer Science (R0)