A new weighted guided image filter was proposed for the problem that guided image filtering fails to preserve sharp edges and leads to excessive structural blurring in smoothed images.Peak-aware weighting was utilized to extract edge and structural information from images,and the robustness of the proposed filter was improved by multi-scale constraints.The regularization term coefficients of the filter loss function were improved to an adaptive form based on the image variance information.Application experiments were carried out in edge-aware smoothing,image detail enhancement,texture removal smoothing,and image denoising,and the results showed that the proposed filter outperformed the guided image filters involved in the comparison in terms of visualization,peak signal-to-noise ratio,and structural similarity.Compared with the peak signal-to-noise ratio and structural similarity of the suboptimal filters of the edge-aware smoothing experiments,the peak signal-to-noise ratio was 2.62 dB higher on average,and the structural similarity was 0.0286 higher on average.
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