| /external/opencv3/modules/features2d/src/kaze/ |
| utils.h | 31 * @brief This function computes the value of a 2D Gaussian function
36 inline float gaussian(float x, float y, float sigma) { function
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| nldiffusion_functions.cpp | 18 * 2D Gaussian Derivatives
39 * @brief This function smoothes an image with a Gaussian kernel
65 // Perform the Gaussian Smoothing with border replication
207 * @param ksize_x Kernel size in X-direction (horizontal) for the Gaussian smoothing kernel
208 * @param ksize_y Kernel size in Y-direction (vertical) for the Gaussian smoothing kernel
222 Mat gaussian = Mat::zeros(img.rows, img.cols, CV_32F); local
226 // Perform the Gaussian convolution
227 gaussian_2D_convolution(img, gaussian, ksize_x, ksize_y, gscale);
229 // Compute the Gaussian derivatives Lx and Ly
230 Scharr(gaussian, Lx, CV_32F, 1, 0, 1, 0, cv::BORDER_DEFAULT)
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| /external/libvpx/libvpx/vp9/common/ |
| vp9_postproc.c | 537 static double gaussian(double sigma, double mu, double x) { function
553 * a gaussian distribution with sigma determined by q.
561 int a_i = (int)(0.5 + 256 * gaussian(sigma, 0, i));
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| /hardware/intel/common/omx-components/videocodec/libvpx_internal/libvpx/vp9/common/ |
| vp9_postproc.c | 374 static double gaussian(double sigma, double mu, double x) { function
390 * a gaussian distribution with sigma determined by q.
399 int a = (int)(0.5 + 256 * gaussian(sigma, 0, i));
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| /external/libvpx/libvpx/vp8/common/ |
| postproc.c | 430 static double gaussian(double sigma, double mu, double x) function
449 * a gaussian distribution with sigma determined by q.
458 const int v = (int)(.5 + 256 * gaussian(sigma, 0, i));
497 * INPUTS : unsigned char *Start starting address of buffer to add gaussian
509 * FUNCTION : adds gaussian noise to a plane of pixels
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| /external/skia/src/effects/ |
| SkBlurMask.cpp | 498 // 6*rad+1 while the full Gaussian width is 6*sigma.
502 // Gaussian blur area (1.5*sigma on each side). The single pass box
508 // to approximate a Gaussian blur
849 // gaussian kernel. It's "ground truth" in a sense; too slow to be used, but very
873 float gaussian = expf(-x*x / (2*variance)); local
874 gaussWindow[halfWindow + x] = gaussWindow[halfWindow-x] = gaussian;
875 windowSum += 2*gaussian;
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| /external/skia/tests/ |
| BlurTest.cpp | 202 // Implement a Gaussian function with 0 mean and std.dev. of 'sigma'.
203 static float gaussian(int x, SkScalar sigma) { function
209 // Perform a brute force convolution of a step function with a Gaussian.
220 sum += gaussian(j, gaussianSigma) * step(i-j, stepMin, stepMax);
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| /external/webrtc/webrtc/common_audio/vad/ |
| vad_core.c | 35 // Start values for the Gaussian models, Q7
114 // Gaussian Mixture Models (GMM). A hypothesis-test is performed to decide which
134 int gaussian; local
185 gaussian = channel + k * kNumChannels;
189 self->noise_means[gaussian],
190 self->noise_stds[gaussian],
191 &deltaN[gaussian]);
192 noise_probability[k] = kNoiseDataWeights[gaussian] * tmp1_s32;
198 self->speech_means[gaussian],
199 self->speech_stds[gaussian],
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| /external/opencv3/modules/core/src/ |
| rand.cpp | 401 double RNG::gaussian(double sigma) function in class:cv::RNG
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| /external/opencv3/modules/video/src/ |
| bgfg_gaussmix2.cpp | 43 /*//Implementation of the Gaussian mixture model background subtraction from:
59 //additional selection of the number of the Gaussian components based on:
92 Interface of Gaussian mixture algorithm from:
105 // default parameters of gaussian background detection algorithm
149 // the number of gaussian mixtures, the background ratio parameter and the noise strength
222 // for each gaussian mixture of each pixel bg model we store ...
514 //additional selection of the number of the Gaussian components based on:
882 GMM gaussian = gmm[gaussianIdx]; local
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