Conference Paper

Multi-Dimensional Denoising of Real-Time Oct Imaging Data

Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL
DOI: 10.1109/ICASSP.2006.1660551 Conference: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on, Volume: 2
Source: IEEE Xplore

ABSTRACT We present a novel scheme for blind suppression of noise from a sequence of optical coherence tomography (OCT) images, such as those collected on a real-time OCT imaging system. In contrast to virtually all existing approaches to OCT denoising, our technique is specifically aimed at collections of images and is able to exploit the correlations among those images. The proposed method approximates the optimal linear denoising operator for log-transformed data using a 2-D discrete wavelet transform (DWT) to decorrelate in space and the discrete Fourier transform (DFT), or an estimated transform, to decorrelate in time. Decorrelated coefficients are then denoised and converted back to the image domain to produce denoised OCT images. Real-time OCT data processed with this technique shows significant reduction in noise

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