Image Smoothing Examples

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Smoothing Results with Varying Parameters

Better smoothing results can be obtained with per-image parameter tweaking.

Input Images

λ=0.005

λ=0.010

λ=0.015

λ=0.020

Input Images

λ=0.010

λ=0.020

λ=0.030

λ=0.040

Input Image

λ=0.005

λ=0.010

λ=0.015

λ=0.020


The following results are produced by successively applying our algorithm with parameters (λ=2.5e-3, κ=1.05) n times. The bottom row shows the color-coded results.

Input Images

n=1

n=5

n=10

n=20

 

Effect Yielded By Successively Applying Local Filtering and Our Algorithm

Our smoothing method can be regarded as complementary to previous local approaches. New effect can be yielded when successively applying local filtering, e.g., bilateral filtering (BLF), and our smoothing method. Details are in the paper.

Input Image

Ours

BLF

BLF+Ours

 

 

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