OpenCV  4.10.0-dev
Open Source Computer Vision
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Classes | Enumerations | Functions
cv::xphoto Namespace Reference

Classes

class  GrayworldWB
 Gray-world white balance algorithm. More...
 
class  LearningBasedWB
 More sophisticated learning-based automatic white balance algorithm. More...
 
class  SimpleWB
 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 \(p\%\) of pixel values. More...
 
class  TonemapDurand
 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. More...
 
class  WhiteBalancer
 The base class for auto white balance algorithms. More...
 

Enumerations

enum  Bm3dSteps {
  BM3D_STEPALL = 0 ,
  BM3D_STEP1 = 1 ,
  BM3D_STEP2 = 2
}
 BM3D algorithm steps. More...
 
enum  InpaintTypes {
  INPAINT_SHIFTMAP = 0 ,
  INPAINT_FSR_BEST = 1 ,
  INPAINT_FSR_FAST = 2
}
 Various inpainting algorithms. More...
 
enum  TransformTypes { HAAR = 0 }
 BM3D transform types. More...
 

Functions

void applyChannelGains (InputArray src, OutputArray dst, float gainB, float gainG, float gainR)
 Implements an efficient fixed-point approximation for applying channel gains, which is the last step of multiple white balance algorithms.
 
void bm3dDenoising (InputArray src, InputOutputArray dstStep1, OutputArray dstStep2, float h=1, int templateWindowSize=4, int searchWindowSize=16, int blockMatchingStep1=2500, int blockMatchingStep2=400, int groupSize=8, int slidingStep=1, float beta=2.0f, int normType=cv::NORM_L2, int step=cv::xphoto::BM3D_STEPALL, int transformType=cv::xphoto::HAAR)
 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.
 
void bm3dDenoising (InputArray src, OutputArray dst, float h=1, int templateWindowSize=4, int searchWindowSize=16, int blockMatchingStep1=2500, int blockMatchingStep2=400, int groupSize=8, int slidingStep=1, float beta=2.0f, int normType=cv::NORM_L2, int step=cv::xphoto::BM3D_STEPALL, int transformType=cv::xphoto::HAAR)
 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.
 
Ptr< GrayworldWBcreateGrayworldWB ()
 Creates an instance of GrayworldWB.
 
Ptr< LearningBasedWBcreateLearningBasedWB (const String &path_to_model=String())
 Creates an instance of LearningBasedWB.
 
Ptr< SimpleWBcreateSimpleWB ()
 Creates an instance of SimpleWB.
 
Ptr< TonemapDurandcreateTonemapDurand (float gamma=1.0f, float contrast=4.0f, float saturation=1.0f, float sigma_color=2.0f, float sigma_space=2.0f)
 Creates TonemapDurand object.
 
void dctDenoising (const Mat &src, Mat &dst, const double sigma, const int psize=16)
 The function implements simple dct-based denoising.
 
void inpaint (const Mat &src, const Mat &mask, Mat &dst, const int algorithmType)
 The function implements different single-image inpainting algorithms.
 
void oilPainting (InputArray src, OutputArray dst, int size, int dynRatio)
 oilPainting See the book [46] for details.
 
void oilPainting (InputArray src, OutputArray dst, int size, int dynRatio, int code)
 oilPainting See the book [46] for details.