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Larger blobs are not 66 affected by the algorithm 67 @param maxDiff Maximum difference between neighbor disparity pixels to put them into the same 68 blob. Note that since StereoBM, StereoSGBM and may be other algorithms return a fixed-point 69 disparity map, where disparity values are multiplied by 16, this scale factor should be taken into 70 account when specifying this parameter value. 71 @param buf The optional temporary buffer to avoid memory allocation within the function. 72 */ 73 /** @brief The base class for stereo correspondence algorithms. 74 */ 75 class StereoMatcher : public Algorithm 76 { 77 public: 78 enum { DISP_SHIFT = 4, 79 DISP_SCALE = (1 << DISP_SHIFT) 80 }; 81 82 /** @brief Computes disparity map for the specified stereo pair 83 84 @param left Left 8-bit single-channel image. 85 @param right Right image of the same size and the same type as the left one. 86 @param disparity Output disparity map. It has the same size as the input images. Some algorithms, 87 like StereoBM or StereoSGBM compute 16-bit fixed-point disparity map (where each disparity value 88 has 4 fractional bits), whereas other algorithms output 32-bit floating-point disparity map. 89 */ 90 virtual void compute( InputArray left, InputArray right, 91 OutputArray disparity ) = 0; 92 93 virtual int getMinDisparity() const = 0; 94 virtual void setMinDisparity(int minDisparity) = 0; 95 96 virtual int getNumDisparities() const = 0; 97 virtual void setNumDisparities(int numDisparities) = 0; 98 99 virtual int getBlockSize() const = 0; 100 virtual void setBlockSize(int blockSize) = 0; 101 102 virtual int getSpeckleWindowSize() const = 0; 103 virtual void setSpeckleWindowSize(int speckleWindowSize) = 0; 104 105 virtual int getSpeckleRange() const = 0; 106 virtual void setSpeckleRange(int speckleRange) = 0; 107 108 virtual int getDisp12MaxDiff() const = 0; 109 virtual void setDisp12MaxDiff(int disp12MaxDiff) = 0; 110 111 }; 112 //!speckle removal algorithms. These algorithms have the purpose of removing small regions 113 enum { 114 CV_SPECKLE_REMOVAL_ALGORITHM, CV_SPECKLE_REMOVAL_AVG_ALGORITHM 115 }; 116 //!subpixel interpolationm methods for disparities. 117 enum{ 118 CV_QUADRATIC_INTERPOLATION, CV_SIMETRICV_INTERPOLATION 119 }; 120 /** @brief Class for computing stereo correspondence using the block matching algorithm, introduced and 121 contributed to OpenCV by K. Konolige. 122 */ 123 class StereoBinaryBM : public StereoMatcher 124 { 125 public: 126 enum { PREFILTER_NORMALIZED_RESPONSE = 0, 127 PREFILTER_XSOBEL = 1 128 }; 129 130 virtual int getPreFilterType() const = 0; 131 virtual void setPreFilterType(int preFilterType) = 0; 132 133 virtual int getPreFilterSize() const = 0; 134 virtual void setPreFilterSize(int preFilterSize) = 0; 135 136 virtual int getPreFilterCap() const = 0; 137 virtual void setPreFilterCap(int preFilterCap) = 0; 138 139 virtual int getTextureThreshold() const = 0; 140 virtual void setTextureThreshold(int textureThreshold) = 0; 141 142 virtual int getUniquenessRatio() const = 0; 143 virtual void setUniquenessRatio(int uniquenessRatio) = 0; 144 145 virtual int getSmallerBlockSize() const = 0; 146 virtual void setSmallerBlockSize(int blockSize) = 0; 147 148 virtual int getScalleFactor() const = 0 ; 149 virtual void setScalleFactor(int factor) = 0; 150 151 virtual int getSpekleRemovalTechnique() const = 0 ; 152 virtual void setSpekleRemovalTechnique(int factor) = 0; 153 154 virtual bool getUsePrefilter() const = 0 ; 155 virtual void setUsePrefilter(bool factor) = 0; 156 157 virtual int getBinaryKernelType() const = 0; 158 virtual void setBinaryKernelType(int value) = 0; 159 160 virtual int getAgregationWindowSize() const = 0; 161 virtual void setAgregationWindowSize(int value) = 0; 162 /** @brief Creates StereoBM object 163 164 @param numDisparities the disparity search range. For each pixel algorithm will find the best 165 disparity from 0 (default minimum disparity) to numDisparities. The search range can then be 166 shifted by changing the minimum disparity. 167 @param blockSize the linear size of the blocks compared by the algorithm. The size should be odd 168 (as the block is centered at the current pixel). Larger block size implies smoother, though less 169 accurate disparity map. Smaller block size gives more detailed disparity map, but there is higher 170 chance for algorithm to find a wrong correspondence. 171 172 The function create StereoBM object. You can then call StereoBM::compute() to compute disparity for 173 a specific stereo pair. 174 */ 175 CV_EXPORTS static Ptr< cv::stereo::StereoBinaryBM > create(int numDisparities = 0, int blockSize = 9); 176 }; 177 178 /** @brief The class implements the modified H. Hirschmuller algorithm @cite HH08 that differs from the original 179 one as follows: 180 181 - By default, the algorithm is single-pass, which means that you consider only 5 directions 182 instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the 183 algorithm but beware that it may consume a lot of memory. 184 - The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the 185 blocks to single pixels. 186 - Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi 187 sub-pixel metric from @cite BT98 is used. Though, the color images are supported as well. 188 - Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for 189 example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness 190 check, quadratic interpolation and speckle filtering). 191 192 @note 193 - (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found 194 at opencv_source_code/samples/python2/stereo_match.py 195 */ 196 class StereoBinarySGBM : public StereoMatcher 197 { 198 public: 199 enum 200 { 201 MODE_SGBM = 0, 202 MODE_HH = 1 203 }; 204 205 virtual int getPreFilterCap() const = 0; 206 virtual void setPreFilterCap(int preFilterCap) = 0; 207 208 virtual int getUniquenessRatio() const = 0; 209 virtual void setUniquenessRatio(int uniquenessRatio) = 0; 210 211 virtual int getP1() const = 0; 212 virtual void setP1(int P1) = 0; 213 214 virtual int getP2() const = 0; 215 virtual void setP2(int P2) = 0; 216 217 virtual int getMode() const = 0; 218 virtual void setMode(int mode) = 0; 219 220 virtual int getSpekleRemovalTechnique() const = 0 ; 221 virtual void setSpekleRemovalTechnique(int factor) = 0; 222 223 virtual int getBinaryKernelType() const = 0; 224 virtual void setBinaryKernelType(int value) = 0; 225 226 virtual int getSubPixelInterpolationMethod() const = 0; 227 virtual void setSubPixelInterpolationMethod(int value) = 0; 228 229 /** @brief Creates StereoSGBM object 230 231 @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes 232 rectification algorithms can shift images, so this parameter needs to be adjusted accordingly. 233 @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than 234 zero. In the current implementation, this parameter must be divisible by 16. 235 @param blockSize Matched block size. It must be an odd number \>=1 . Normally, it should be 236 somewhere in the 3..11 range. 237 @param P1 The first parameter controlling the disparity smoothness.This parameter is used for the case of slanted surfaces (not fronto parallel). 238 @param P2 The second parameter controlling the disparity smoothness.This parameter is used for "solving" the depth discontinuities problem. 239 The larger the values are, the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 240 between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor 241 pixels. The algorithm requires P2 \> P1 . See stereo_match.cpp sample where some reasonably good 242 P1 and P2 values are shown (like 8\*number_of_image_channels\*SADWindowSize\*SADWindowSize and 243 32\*number_of_image_channels\*SADWindowSize\*SADWindowSize , respectively). 244 @param disp12MaxDiff Maximum allowed difference (in integer pixel units) in the left-right 245 disparity check. Set it to a non-positive value to disable the check. 246 @param preFilterCap Truncation value for the prefiltered image pixels. The algorithm first 247 computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. 248 The result values are passed to the Birchfield-Tomasi pixel cost function. 249 @param uniquenessRatio Margin in percentage by which the best (minimum) computed cost function 250 value should "win" the second best value to consider the found match correct. Normally, a value 251 within the 5-15 range is good enough. 252 @param speckleWindowSize Maximum size of smooth disparity regions to consider their noise speckles 253 and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the 254 50-200 range. 255 @param speckleRange Maximum disparity variation within each connected component. If you do speckle 256 filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. 257 Normally, 1 or 2 is good enough. 258 @param mode Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming 259 algorithm. It will consume O(W\*H\*numDisparities) bytes, which is large for 640x480 stereo and 260 huge for HD-size pictures. By default, it is set to false . 261 262 The first constructor initializes StereoSGBM with all the default parameters. So, you only have to 263 set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter 264 to a custom value. 265 */ 266 CV_EXPORTS static Ptr<cv::stereo::StereoBinarySGBM> create(int minDisparity, int numDisparities, int blockSize, 267 int P1 = 100, int P2 = 1000, int disp12MaxDiff = 1, 268 int preFilterCap = 0, int uniquenessRatio = 5, 269 int speckleWindowSize = 400, int speckleRange = 200, 270 int mode = StereoBinarySGBM::MODE_SGBM); 271 }; 272 //! @} 273 }//stereo 274 } // cv 275 276 #endif 277