Expand description
Modules
Structs
- Gray-world white balance algorithm
- More sophisticated learning-based automatic white balance algorithm.
- A simple white balance algorithm that works by independently stretching each of the input image channels to the specified range. For increased robustness it ignores the top and bottom inline formula of pixel values.
- This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter and compresses contrast of the base layer thus preserving all the details.
- The base class for auto white balance algorithms.
Enums
- BM3D algorithm steps
- Various inpainting algorithms
- BM3D transform types
Constants
- Execute only first step of the algorithm
- Execute only second step of the algorithm
- Execute all steps of the algorithm
- Un-normalized Haar transform
- Performs Frequency Selective Reconstruction (FSR). One of the two quality profiles BEST and FAST can be chosen, depending on the time available for reconstruction. See GenserPCS2018 and SeilerTIP2015 for details.
- See #INPAINT_FSR_BEST
- This algorithm searches for dominant correspondences (transformations) of image patches and tries to seamlessly fill-in the area to be inpainted using this transformations
Traits
- Mutable methods for crate::xphoto::GrayworldWB
- Constant methods for crate::xphoto::GrayworldWB
- Mutable methods for crate::xphoto::LearningBasedWB
- Constant methods for crate::xphoto::LearningBasedWB
- Mutable methods for crate::xphoto::SimpleWB
- Constant methods for crate::xphoto::SimpleWB
- Mutable methods for crate::xphoto::TonemapDurand
- Constant methods for crate::xphoto::TonemapDurand
- Mutable methods for crate::xphoto::WhiteBalancer
- Constant methods for crate::xphoto::WhiteBalancer
Functions
- Implements an efficient fixed-point approximation for applying channel gains, which is the last step of multiple white balance algorithms.
- Performs image denoising using the Block-Matching and 3D-filtering algorithm http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf with several computational optimizations. Noise expected to be a gaussian white noise.
- Performs image denoising using the Block-Matching and 3D-filtering algorithm http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf with several computational optimizations. Noise expected to be a gaussian white noise.
- Creates an instance of GrayworldWB
- Creates an instance of LearningBasedWB
- Creates an instance of SimpleWB
- Creates TonemapDurand object
- The function implements simple dct-based denoising
- The function implements different single-image inpainting algorithms.
- oilPainting See the book Holzmann1988 for details.
- oilPainting See the book Holzmann1988 for details.