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Real-Time Noise Reduction Algorithm for Video with Non-linear FIR Filter

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1118))

Abstract

Noise is an essential issue for images and videos. Recently, a range of high-sensitivity imaging devices have become available. Cameras are often used under poor lighting conditions for security purposes or night time news gathering. Videos shot under poor lighting conditions are afflicted by significant noise which degrades the image quality. The process of noise removal from videos is called noise reduction (NR). Although many NR methods are proposed, they are complex and are proposed as computer simulations. In practical applications, NR processing of videos occurs in real-time. The practical real-time methods are limited and the complex NR methods cannot cope with real-time processing. Video has three dimensions: horizontal, vertical and temporal. Since the temporal relation is stronger than that of horizontal and vertical, the conventional real-time NR methods use the temporal infinite impulse response (IIR) filter to reduce noise. This approach is known as the inter-frame relation, and the noise reducer comprises a temporal recursive filter. Temporal recursive filters are widely used in digital TV sets to reduce the noise affecting images. Although the temporal recursive filter is a simple algorithm, moving objects leave trails when it reduces the high-level noise. In this paper, a novel NR algorithm is introduced. The proposed method uses finite impulse response (FIR) filter. The FIR filter does not suffer from this trail issue and shows better performance than NR using temporal recursive filters is proposed.

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Correspondence to Seiichi Gohshi .

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Gohshi, S., Mori, C. (2019). Real-Time Noise Reduction Algorithm for Video with Non-linear FIR Filter. In: Obaidat, M. (eds) E-Business and Telecommunications. ICETE 2018. Communications in Computer and Information Science, vol 1118. Springer, Cham. https://doi.org/10.1007/978-3-030-34866-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-34866-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34865-6

  • Online ISBN: 978-3-030-34866-3

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