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12 April 2021 Discrete legendre polynomial based adaptive image filtering
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Adaptive image filtering, removing noises without blurring the discontinuity of images, is important for many image processing, pattern recognition and computer vision applications. Many researches including anisotropic diffusion equation techniques have been conducted to address adaptive image filtering problems. Traditional techniques usually use differential characteristics of images to determine filtering coefficients for adaptively filtering images. As is well known, differential characteristics are difficult to estimate and the techniques to compute differential characteristics are usually sensitive to noises due to the intrinsic properties of derivatives. In this paper, we propose discrete Legendre polynomial based adaptive image filtering that effectively remove noises with preserving discontinuity of edges. We use polynomial fitting errors to choose masks to achieve the adaptivity. The fitting errors are computed by integrals (summation). This overcomes the derivative noise-sensitivity problems and allows us to achieve high performance.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bingcheng Li "Discrete legendre polynomial based adaptive image filtering", Proc. SPIE 11729, Automatic Target Recognition XXXI, 117290W (12 April 2021);


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