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Diffstat (limited to 'intern/libmv/libmv/image/convolve.h')
| -rw-r--r-- | intern/libmv/libmv/image/convolve.h | 107 |
1 files changed, 107 insertions, 0 deletions
diff --git a/intern/libmv/libmv/image/convolve.h b/intern/libmv/libmv/image/convolve.h new file mode 100644 index 00000000000..d3b6da9794b --- /dev/null +++ b/intern/libmv/libmv/image/convolve.h @@ -0,0 +1,107 @@ +// Copyright (c) 2007, 2008, 2011 libmv authors. +// +// Permission is hereby granted, free of charge, to any person obtaining a copy +// of this software and associated documentation files (the "Software"), to +// deal in the Software without restriction, including without limitation the +// rights to use, copy, modify, merge, publish, distribute, sublicense, and/or +// sell copies of the Software, and to permit persons to whom the Software is +// furnished to do so, subject to the following conditions: +// +// The above copyright notice and this permission notice shall be included in +// all copies or substantial portions of the Software. +// +// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS +// IN THE SOFTWARE. + +#ifndef LIBMV_IMAGE_CONVOLVE_H_ +#define LIBMV_IMAGE_CONVOLVE_H_ + +#include "libmv/image/image.h" +#include "libmv/numeric/numeric.h" + +namespace libmv { + +// TODO(keir): Find a better place for these functions. gaussian.h in numeric? + +// Zero mean Gaussian. +inline double Gaussian(double x, double sigma) { + return 1/sqrt(2*M_PI*sigma*sigma) * exp(-(x*x/2/sigma/sigma)); +} +// 2D gaussian (zero mean) +// (9) in http://mathworld.wolfram.com/GaussianFunction.html +inline double Gaussian2D(double x, double y, double sigma) { + return 1.0/(2.0*M_PI*sigma*sigma) * exp( -(x*x+y*y)/(2.0*sigma*sigma)); +} +inline double GaussianDerivative(double x, double sigma) { + return -x / sigma / sigma * Gaussian(x, sigma); +} +// Solve the inverse of the Gaussian for positive x. +inline double GaussianInversePositive(double y, double sigma) { + return sqrt(-2 * sigma * sigma * log(y * sigma * sqrt(2*M_PI))); +} + +void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative); +void ConvolveHorizontal(const FloatImage &in, + const Vec &kernel, + FloatImage *out_pointer, + int plane = -1); +void ConvolveVertical(const FloatImage &in, + const Vec &kernel, + FloatImage *out_pointer, + int plane = -1); +void ConvolveGaussian(const FloatImage &in, + double sigma, + FloatImage *out_pointer); + +void ImageDerivatives(const FloatImage &in, + double sigma, + FloatImage *gradient_x, + FloatImage *gradient_y); + +void BlurredImageAndDerivatives(const FloatImage &in, + double sigma, + FloatImage *blurred_image, + FloatImage *gradient_x, + FloatImage *gradient_y); + +// Blur and take the gradients of an image, storing the results inside the +// three channels of blurred_and_gradxy. +void BlurredImageAndDerivativesChannels(const FloatImage &in, + double sigma, + FloatImage *blurred_and_gradxy); + +void BoxFilterHorizontal(const FloatImage &in, + int window_size, + FloatImage *out_pointer); + +void BoxFilterVertical(const FloatImage &in, + int window_size, + FloatImage *out_pointer); + +void BoxFilter(const FloatImage &in, + int box_width, + FloatImage *out); + +/*! + Convolve \a src into \a dst with the discrete laplacian operator. + + \a src and \a dst should be \a width x \a height images. + \a strength is an interpolation coefficient (0-256) between original image and the laplacian. + + \note Make sure the search region is filtered with the same strength as the pattern. +*/ +void LaplaceFilter(unsigned char* src, + unsigned char* dst, + int width, + int height, + int strength); + +} // namespace libmv + +#endif // LIBMV_IMAGE_CONVOLVE_H_ + |