Adaptive weighted guided image filtering for depth enhancement in shape-from-focus

Guided Image Filtering for Image Enhancement

Noise removing belongs to image restoration in digital image processing. It’s the essential guarantee of identifying image information and the reliable guarantee of making further image processing. A satisfying result can’t be found if processing method such as feature extraction, registration or image fusion is carried out on an image with noise. So removing noise is absolutely necessary for i...

Guided Filters for Depth Image Enhancement

Light Field Assisted Stereo Matching using Depth from Focus and Image-Guided Cost-Volume Filtering

Light field photography advances upon current digital imaging technology by making it possible to adjust focus after capturing a photograph. This capability is enabled by an array of microlenses mounted above the image sensor, allowing the camera to simultaneously capture both light intensity and approximate angle of incidence. The ability to adjust focus after capture makes light field photogr...

Image Enhancement Using Adaptive Filtering

In this paper, we develop an image enhancement algorithm that modifies the local luminance mean of an image and controls the local contrast as a function of the local luminance mean of the image. The algorithm first separates an image into its lows (low pass filtered form) and highs (high pass filtered form) components. The lows component then controls the amplitude of the highs component to in...

Weighted Guided Image Filtering – A Survey

It is well-known that local filtering-based edge preserving smoothing method suffers from halo artifacts. In this paper, a weighted guided image filter is introduced by incorporating an edge-aware weighting into an accessible guided image filter to address the problem. The WGIF inherit benefits of both global and local smoothing filters in the sense that: 1) the difficulty of the WGIF is O(N) f...