Content-Dependent Scan Rate Converter with Adaptive Noise Reduction

作者: Arnold P. Skoog , Jeffrey Kempf , Clifford D. Fairbanks

DOI:

关键词: Artificial intelligenceValue noiseMathematicsNoise reductionComputer visionNoise measurementGradient noiseMedian filterGaussian noiseImage noiseSalt-and-pepper noise

摘要: A content-dependent scan rate converter with adaptive noise reduction that provides a highly integrated, implementation efficient de-interlacer. By identifying and using redundant information from the image (motion values edge directions), this is able to perform tasks of film-mode detection, motion-adaptive conversion, video reduction. Adaptive incorporated in process where temporal performed on still parts image, thus preserving high detail spatial information, data-adaptive moving image. low-pass filter used flat fields smooth out Gaussian direction-dependent median presence impulsive or an edge. Therefore, selected optimized for particular pixel being processed maintain crisp edges.

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