Weighted Guided Image Filtering - 2015 PROJECT TITLE : Weighted Guided Image Filtering - 2015 ABSTRACT: It's known that local filtering-primarily based edge preserving smoothing techniques suffer from halo artifacts. In this paper, a weighted guided image filter (WGIF) is introduced by incorporating a footing-aware weighting into an existing guided image filter (GIF) to deal with the problem. The WGIF inherits blessings of each global and local smoothing filters in the way that: one) the complexity of the WGIF is O(N) for a picture with N pixels, that is same because the GIF and a couple of) the WGIF can avoid halo artifacts like the prevailing global smoothing filters. The WGIF is applied for single image detail enhancement, single image haze removal, and fusion of differently exposed pictures. Experimental results show that the resultant algorithms turn out pictures with better visual quality and at the identical time halo artifacts will be reduced/avoided from appearing in the ultimate images with negligible increment on running times. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Filtering Theory Image Enhancement Edge Detection Exposure Fusion Edge-Preserving Smoothing Weighted Guided Image Filter Edge-Aware Weighting Detail Enhancement Haze Removal Matching of Large Images Through Coupled Decomposition - 2015 Hierarchical Graphical Models for Simultaneous Tracking and Recognition in Wide-Area Scenes - 2015
