A local variance-based bilateral filtering for artifact-free detail- and edge-preserving smoothing

Authors:
Cuong Cao Pham;Synh Viet Uyen Ha;Jae Wook Jeon
Affiliations:
School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea
Venue:
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Year:
2011

Citing 23
Cited 0

Scale-Space and Edge Detection Using Anisotropic Diffusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN—A New Approach to Low Level Image Processing

International Journal of Computer Vision
LCIS: a boundary hierarchy for detail-preserving contrast reduction

Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Fast bilateral filtering for the display of high-dynamic-range images

Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A Fundamental Relationship between Bilateral Filtering, Adaptive Smoothing, and the Nonlinear Diffusion Equation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-Linear Gaussian Filters Performing Edge Preserving Diffusion

Mustererkennung 1995, 17. DAGM-Symposium
The trilateral filter for high contrast images and meshes

EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
Bilateral Filtering for Gray and Color Images

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Colorization using optimization

ACM SIGGRAPH 2004 Papers
A Non-Local Algorithm for Image Denoising

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Real-time edge-aware image processing with the bilateral grid

ACM SIGGRAPH 2007 papers
Fast communication: Adaptive bilateral filtering of image signals using local phase characteristics

Signal Processing
Edge-preserving decompositions for multi-scale tone and detail manipulation

ACM SIGGRAPH 2008 papers
A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach

International Journal of Computer Vision
Edge-preserving multiscale image decomposition based on local extrema

ACM SIGGRAPH Asia 2009 papers
Smoothed local histogram filters

ACM SIGGRAPH 2010 papers
Bilateral Filtering

Bilateral Filtering
Guided image filtering

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Robust anisotropic diffusion

IEEE Transactions on Image Processing
On the origin of the bilateral filter and ways to improve it

IEEE Transactions on Image Processing
The staircasing effect in neighborhood filters and its solution

IEEE Transactions on Image Processing
Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removal

IEEE Transactions on Image Processing
Bi-affinity filter: a bilateral type filter for color images

ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.