Abstract
In this paper we present a wavelet-based video enhancement algorithm designed for highly optimized dedicated ICs. The proposed algorithm is implemented on FPGA platform with target being real-time video processing. The main application of the proposed scheme is a high definition (HD) TV, where we consider visibly annoying video coding artifacts and noise (assumed as white Gaussian).
In the proposed denoising scheme each video frame is processed independently, i.e., only spatial filtering is performed. Specifically, two-dimensional (2D) non-decimated wavelet transform is applied to the frame, after which the proposed activity-adaptive shrinkage operation on the wavelet coefficients is done. Finally, the denoised image is reconstructed by inverse wavelet transform. The main contribution of the paper is the proposed (i) hardware-friendly scheme for the wavelet decomposition - reconstruction framework with full parallelism and reduced memory resources required and (ii) efficient and low computationally expensive activity-adaptive shrinkage algorithm for denoising.
The designed framework is verified in SystemC and on FPGA platform with WXGA Panel. The annoying artifacts and noise are shown to be efficiently removed with small or no visible reduction in spatial resolution.
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Zlokolica, V., Katona, M., Juenke, M., Krajacevic, Z., Teslic, N., Temerinac, M. (2008). Real-Time Wavelet-Spatial-Activity-Based Adaptive Video Enhancement Algorithm for FPGA. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_17
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DOI: https://doi.org/10.1007/978-3-540-88458-3_17
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