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Edge-preserving smoothing has recently emerged as a crucial technique for a variety of computer vision and image processing applications. The idea is to smooth the small scale variations, while preserving edges and fine details in the image, without causing halo artifacts in detail enhancement. In this paper, we propose a modified bilateral filter model that has better behavior near edges and details than the standard model does. The edge-stopping function takes into account the intensity difference and the local variance of the filter windows, which provides insightful information about the local pixel distribution. We demonstrate the existing detail-related bilateral-based applications can achieve better results by simply switching from the standard model to our proposed model. In particular, we applied our method to detail-preserving image denoising and detail enhancement.

A Local Variance-Based Bilateral Filtering for Artifact-Free Detail- and Edge-Preserving Smoothing