To eliminate halo artifacts produced by guided image filtering

this paper proposes a novel

improved

guided image filter that is integrated with gradient information. Our method uses gradient information of guidance images to determine edge positions

and designs the weight model based on an exponential function to control the smoothness of different image regions. It makes an improved guided image filter that adaptively finds edges and emphasizes them

thereby avoiding the halo introduced by excessive smooth near edges. Experiments show that our method can avoid halo artifacts during periods of edge-preserving smoothing

and respectively attains approximately 30% and 15% higher advancement for SSIM and PSNR

compared with the guided image filter. Our method has greater robustness and performance in many computer vision and computer graphics applications such as image smoothing

detail enhancement

and multi-exposure fusion.