Discrete legendre polynomial based adaptive image filtering

Bingcheng Li

doi:10.1117/12.2588241

12 April 2021 Discrete legendre polynomial based adaptive image filtering

Bingcheng Li

Author Affiliations +

Proceedings Volume 11729, Automatic Target Recognition XXXI; 117290W (2021) https://doi.org/10.1117/12.2588241
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

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

Citation Download Citation

Bingcheng Li "Discrete legendre polynomial based adaptive image filtering", Proc. SPIE 11729, Automatic Target Recognition XXXI, 117290W (12 April 2021); https://doi.org/10.1117/12.2588241

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