15 February 2006 Real-time image denoising algorithm in teleradiology systems
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Proceedings Volume 6063, Real-Time Image Processing 2006; 606304 (2006); doi: 10.1117/12.650595
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.
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Pradeep Kumar Gupta, Rajan Kanhirodan, "Real-time image denoising algorithm in teleradiology systems", Proc. SPIE 6063, Real-Time Image Processing 2006, 606304 (15 February 2006); doi: 10.1117/12.650595; https://doi.org/10.1117/12.650595
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KEYWORDS
Wavelets

Wavelet transforms

Medical imaging

Image restoration

Teleradiology

Denoising

Image denoising

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