OpenCV
3.4.5
Open Source Computer Vision
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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 } |
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. More... | |
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. More... | |
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. More... | |
Ptr< GrayworldWB > | createGrayworldWB () |
Creates an instance of GrayworldWB. More... | |
Ptr< LearningBasedWB > | createLearningBasedWB (const String &path_to_model=String()) |
Creates an instance of LearningBasedWB. More... | |
Ptr< SimpleWB > | createSimpleWB () |
Creates an instance of SimpleWB. More... | |
Ptr< TonemapDurand > | createTonemapDurand (float gamma=1.0f, float contrast=4.0f, float saturation=1.0f, float sigma_space=2.0f, float sigma_color=2.0f) |
Creates TonemapDurand object. More... | |
void | dctDenoising (const Mat &src, Mat &dst, const double sigma, const int psize=16) |
The function implements simple dct-based denoising. More... | |
void | inpaint (const Mat &src, const Mat &mask, Mat &dst, const int algorithmType) |
The function implements different single-image inpainting algorithms. More... | |