摘要(英) |
High- definition display has become the mainstream of media player, but most of the current distribution of video content is not premise of making High-definition video quality, using scaler to enlarge the input video resolution is a common solution today, the core of scaler shall be interpolator.
This paper developed a probabilistic neural network-based intelligent video interpolator. This interpolator analysis of image in the region around the each interpolation point sharpness, according to the evaluation value of sharpness as a single neuron input to adjust the smoothing parameter of PNN interpolator, finally using PNN interpolator to do it. The probabilistic neural network-based intelligent video interpolator has to adapt to different characteristics of video interpolation region, it provides more sharp effect near the edge, and in the smooth region, to enhance smooth effect is provide. Compared with conventional video scaler, the system shows a very excellent scaled image quality.
This intelligent video scaler has verified its functional correctness and performance in the FPGA test platform. Apart from implement PNN interpolator hardware circuit, we also completed the memory controller, LCD controller, image processor, finally design a pipeline controller for each of the parallel hardware architecture module integrated into the video scaling chip. The chip uses only 2147 Logic Elements and 241k bits of memory on FPGA hardware resources, and can reach 30 frames 1920x1080 images per second interpolation rate, indicating the system has satisfactory performance. The research results will be used in digital television, high-definition video surveillance and portable media player devices.
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參考文獻 |
[1] R. S. Prodan,”Multidimensional Digital Signal Processing For Television Scan Conversion” Philips J. Res. 41,pp.576-603,1986.
[2] D. Nquyen, E. Dubois,”Spatio-Temporal Adaptive Interlaced To Progressive Conversion”,International Workshop On HDTV’92 Proceeding Vol. 2, 18-20, Nov.1992.
[3] X. Li, M.T. Orchard, “New Edge-Directed Interpolation”, IEEE Trans. on Image Processing, vol. 10, pp. 1521-1527, Oct. 2001.
[4] S. H. Hsieh; C. H. Chen, “Adaptive image interpolation using probabilistic neural network”, Expert Systems with Applications, vol.36, issue.3, part.2, pp. 6025-6029, April 2009.
[5] Ching-Han CHEN; Jia_Hong DAI “Design and High-Level Synthesis of Discrete-Event Controller”, Automatic Control Conference, Page(s): 610 –615. 2002
[6] Gribbon, K.T.; Bailey, D.G “Electronic Design, Test and Applications, 2004. DELTA 2004. Second IEEE International Workshop on”, Digital Object Identifier 10.1109/DELTA.2004.10055, Page(s):126 – 131, 28-30 Jan. 2004
[7] H. Rabtanen, “Color Video Signal Processing With Median Filters”, IEEE Trans, On Consumed Electrons, Vol. 38,No. 3,pp. 157-161,Aug. 1992.
[8] Rafael C. Gonzalez, Ricbard E. Woods, ”Digital Image Processing”, Addison Wesley Publishing Company, pp. 191-200, 1992.
[9] Hee-Chul Kim1, Byong-Heon Kwon2, Myung-Ryul Choi ”An Image Interpolation With Image Improvement For LCD Controller”,1ASIC Lab., Dept. Of EECI,Hanyang University 17 Hangdang-Dong,Seongdong-Ku,Seoul,133-791,Korea
[10] H. B. KWON et al. “Pseudomedian Character For De-Interlacing Scan Conversion”, Journal Of Korea telecommunication Society,Vol. 21,No. 1,pp. 1151-1171,1996.
[11] http://www.issi.com/pdf/42S16400D.pdf
[12] http://www.ddwg.org/lib/dvi_10.pdf
[13] D.F. Specht “Probabilistic neural networks(original contribution) ” Neural Networks .vol. 3, no.1, pp. 109-118, Jan 1990.
[14] Mayer R.J, "IDEF0 Function Modeling", Air Force Systems Command, May, 1992.
[15] IEC, International Electrotechnic Commission, Preparation of Function Charts for Control Systems, publication 848, 1988.
[16] C. A. Petri, Kommunikation mit Automaten, Schriften des Rheinisch, Westfalischen Institutes fur Intrumentelle Mathematik and Der Universitat Bonn, 1962, translation by C. F. Greene, Applied Data Research Inc., Suppl. 1 to Tech Report RADC-TR-65-337, N.Y., 1965.
[17] Keith Jack, "Video Demystified", A Handbook for the Digital Engineer Fourth Edition, 2005.
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