Guided Image Filtering

In this paper, we propose a novel explicit image filter called guided filter. Derived from a local linear model, the guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or another different image. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter [1], but it has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: It can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and nonapproximate linear time algorithm, regardless of the kernel size and the intensity range. Currently, it is one of the fastest edge-preserving filters. Experiments show that the guided filter is both effective and efficient in a great variety of computer vision and computer graphics applications, including edge-aware smoothing, detail enhancement, HDR compression, image matting/feathering, dehazing, joint upsampling, etc.

[1]  Norman R. Draper,et al.  Applied regression analysis (2. ed.) , 1981, Wiley series in probability and mathematical statistics.

[2]  Franklin C. Crow,et al.  Summed-area tables for texture mapping , 1984, SIGGRAPH.

[3]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[5]  R. Deriche.  Recursively Implementing the Gaussian and its Derivatives , 1993 .

[6]  Jörg Weule,et al.  Non-Linear Gaussian Filters Performing Edge Preserving Diffusion , 1995, DAGM-Symposium.

[7]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[8]  Richard F. Gunst,et al.  Applied Regression Analysis , 1999, Technometrics.

[9]  Yair Weiss,et al.  Segmentation using eigenvectors: a unifying view , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[10]  William L. Briggs,et al.  A multigrid tutorial, Second Edition , 2000 .

[11]  Michael Elad,et al.  On the origin of the bilateral filter and ways to improve it , 2002, IEEE Trans. Image Process..

[12]  Alexei A. Efros,et al.  Fast bilateral filtering for the display of high-dynamic-range images , 2002 .

[13]  Shmuel Peleg,et al.  Multi-sensor super-resolution , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[14]  Dani Lischinski,et al.  Gradient Domain High Dynamic Range Compression , 2023 .

[15]  Patrick Pérez,et al.  Poisson image editing , 2003, ACM Trans. Graph..

[16]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[17]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[18]  Stephen M. Smith,et al.  SUSAN—A New Approach to Low Level Image Processing , 1997, International Journal of Computer Vision.

[19]  Jiaya Jia,et al.  Poisson matting , 2004, SIGGRAPH 2004.

[20]  Dani Lischinski,et al.  Colorization using optimization , 2004, ACM Trans. Graph..

[21]  Michael F. Cohen,et al.  Digital photography with flash and no-flash image pairs , 2004, ACM Trans. Graph..

[22]  In-So Kweon,et al.  Adaptive Support-Weight Approach for Correspondence Search , 2006, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Ben Weiss.  Fast median and bilateral filtering , 2006, SIGGRAPH 2006.

[24]  Frédo Durand,et al.  Two-scale tone management for photographic look , 2006, ACM Trans. Graph..

[25]  R. Szeliski.  Locally adapted hierarchical basis preconditioning , 2006, SIGGRAPH '06.

[26]  Leo Grady,et al.  Random Walks for Image Segmentation , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  B. Gooch,et al.  Real-time video abstraction , 2006, ACM Trans. Graph..

[28]  Richard Szeliski,et al.  Noise Estimation from a Single Image , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[29]  Holger Winnemöller,et al.  Real-time video abstraction , 2006, SIGGRAPH 2006.

[30]  Frédo Durand,et al.  A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach , 2006, International Journal of Computer Vision.

[31]  Sylvain Paris,et al.  Real-time edge-aware image processing with the bilateral grid , 2007, ACM Trans. Graph..

[32]  Alessandro Foi,et al.  Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.

[33]  Dani Lischinski,et al.  Joint bilateral upsampling , 2007, SIGGRAPH 2007.

[34]  Szymon Rusinkiewicz,et al.  Multiscale shape and detail enhancement from multi-light image collections , 2007, ACM Trans. Graph..

[35]  Patrick Hébert,et al.  Median Filtering in Constant Time , 2007, IEEE Transactions on Image Processing.

[36]  Michael F. Cohen,et al.  Fourier Analysis of the 2D Screened Poisson Equation for Gradient Domain Problems , 2008, ECCV.

[37]  Jian Sun,et al.  Progressive inter-scale and intra-scale non-blind image deconvolution , 2008, SIGGRAPH 2008.

[38]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Zeev Farbman,et al.  Edge-preserving decompositions for multi-scale tone and detail manipulation , 2008, ACM Trans. Graph..

[40]  Fatih Porikli,et al.  Constant time O(1) bilateral filtering , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[41]  Junfeng Yang,et al.  A New Alternating Minimization Algorithm for Total Variation Image Reconstruction , 2008, SIAM J. Imaging Sci..

[42]  Raanan Fattal,et al.  Edge-avoiding wavelets and their applications , 2009, ACM Trans. Graph..

[43]  S. Osher,et al.  A new median formula with applications to PDE based denoising , 2009 .

[44]  Marc Levoy,et al.  Gaussian KD-trees for fast high-dimensional filtering , 2009, ACM Trans. Graph..

[45]  Jaakko Astola,et al.  From Local Kernel to Nonlocal Multiple-Model Image Denoising , 2009, International Journal of Computer Vision.

[46]  N. Ahuja,et al.  Real-time O(1) bilateral filtering , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[47]  Jian Sun,et al.  Fast matting using large kernel matting Laplacian matrices , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[48]  Andrew Adams,et al.  Fast High‐Dimensional Filtering Using the Permutohedral Lattice , 2010, Comput. Graph. Forum.

[49]  M. Kass,et al.  Smoothed local histogram filters , 2010, ACM Trans. Graph..

[50]  Jian Sun,et al.  Guided Image Filtering , 2010, ECCV.

[51]  Cewu Lu,et al.  Image smoothing via L0 gradient minimization , 2011, ACM Trans. Graph..

[52]  Stefano Mattoccia,et al.  Linear stereo matching , 2011, 2011 International Conference on Computer Vision.

[53]  Jing Xiao,et al.  Importance filtering for image retargeting , 2011, CVPR 2011.

[54]  Jian Sun,et al.  A global sampling method for alpha matting , 2011, CVPR 2011.

[55]  Marcus A. Magnor,et al.  Eurographics Symposium on Rendering 2011 Guided Image Filtering for Interactive High-quality Global Illumination , 2022 .

[56]  Manuel Menezes de Oliveira Neto,et al.  Domain transform for edge-aware image and video processing , 2011, ACM Trans. Graph..

[57]  Carsten Rother,et al.  Fast cost-volume filtering for visual correspondence and beyond , 2011, CVPR 2011.

[58]  Jan Kautz,et al.  Local Laplacian filters: edge-aware image processing with a Laplacian pyramid , 2011, ACM Trans. Graph..

[59]  Manuel Menezes de Oliveira Neto,et al.  Adaptive manifolds for real-time high-dimensional filtering , 2012, ACM Trans. Graph..