9 #ifndef BOOST_GIL_IMAGE_PROCESSING_NUMERIC_HPP 10 #define BOOST_GIL_IMAGE_PROCESSING_NUMERIC_HPP 12 #include <boost/gil/image_processing/kernel.hpp> 13 #include <boost/gil/image_processing/convolve.hpp> 14 #include <boost/gil/image_view.hpp> 15 #include <boost/gil/typedefs.hpp> 16 #include <boost/gil/detail/math.hpp> 21 namespace boost {
namespace gil {
34 inline double normalized_sinc(
double x)
36 return std::sin(x * boost::gil::detail::pi) / (x * boost::gil::detail::pi);
46 inline double lanczos(
double x, std::ptrdiff_t a)
52 if (static_cast<double>(-a) < x && x < static_cast<double>(a))
53 return normalized_sinc(x) / normalized_sinc(x / static_cast<double>(a));
58 #if BOOST_WORKAROUND(BOOST_MSVC, >= 1400) 60 #pragma warning(disable:4244) // 'argument': conversion from 'const Channel' to 'BaseChannelValue', possible loss of data 63 inline void compute_tensor_entries(
64 boost::gil::gray16s_view_t dx,
65 boost::gil::gray16s_view_t dy,
66 boost::gil::gray32f_view_t m11,
67 boost::gil::gray32f_view_t m12_21,
68 boost::gil::gray32f_view_t m22)
70 for (std::ptrdiff_t y = 0; y < dx.height(); ++y) {
71 for (std::ptrdiff_t x = 0; x < dx.width(); ++x) {
72 auto dx_value = dx(x, y);
73 auto dy_value = dy(x, y);
74 m11(x, y) = dx_value * dx_value;
75 m12_21(x, y) = dx_value * dy_value;
76 m22(x, y) = dy_value * dy_value;
81 #if BOOST_WORKAROUND(BOOST_MSVC, >= 1400) 91 template <
typename T =
float,
typename Allocator = std::allocator<T>>
95 if (side_length % 2 != 1)
96 throw std::invalid_argument(
"kernel dimensions should be odd and equal");
97 const float entry = 1.0f / static_cast<float>(side_length * side_length);
100 for (
auto& cell: result) {
111 template <
typename T =
float,
typename Allocator = std::allocator<T>>
115 if (side_length % 2 != 1)
116 throw std::invalid_argument(
"kernel dimensions should be odd and equal");
119 for (
auto& cell: result) {
131 template <
typename T =
float,
typename Allocator = std::allocator<T>>
135 if (side_length % 2 != 1)
136 throw std::invalid_argument(
"kernel dimensions should be odd and equal");
138 const double denominator = 2 * boost::gil::detail::pi * sigma * sigma;
139 auto middle = side_length / 2;
140 std::vector<T, Allocator> values(side_length * side_length);
141 for (std::size_t y = 0; y < side_length; ++y)
143 for (std::size_t x = 0; x < side_length; ++x)
145 const auto delta_x = middle > x ? middle - x : x - middle;
146 const auto delta_y = middle > y ? middle - y : y - middle;
147 const double power = (delta_x * delta_x + delta_y * delta_y) / (2 * sigma * sigma);
148 const double nominator = std::exp(-power);
149 const float value = static_cast<float>(nominator / denominator);
150 values[y * side_length + x] = value;
164 template <
typename T =
float,
typename Allocator = std::allocator<T>>
172 return detail::get_identity_kernel<T, Allocator>();
177 std::copy(detail::dx_sobel.begin(), detail::dx_sobel.end(), result.begin());
181 throw std::logic_error(
"not supported yet");
185 throw std::runtime_error(
"unreachable statement");
195 template <
typename T =
float,
typename Allocator = std::allocator<T>>
203 return detail::get_identity_kernel<T, Allocator>();
208 std::copy(detail::dx_scharr.begin(), detail::dx_scharr.end(), result.begin());
212 throw std::logic_error(
"not supported yet");
216 throw std::runtime_error(
"unreachable statement");
226 template <
typename T =
float,
typename Allocator = std::allocator<T>>
234 return detail::get_identity_kernel<T, Allocator>();
239 std::copy(detail::dy_sobel.begin(), detail::dy_sobel.end(), result.begin());
243 throw std::logic_error(
"not supported yet");
247 throw std::runtime_error(
"unreachable statement");
257 template <
typename T =
float,
typename Allocator = std::allocator<T>>
265 return detail::get_identity_kernel<T, Allocator>();
270 std::copy(detail::dy_scharr.begin(), detail::dy_scharr.end(), result.begin());
274 throw std::logic_error(
"not supported yet");
278 throw std::runtime_error(
"unreachable statement");
290 template <
typename GradientView,
typename OutputView>
300 detail::convolve_2d(dx, sobel_x, ddxx);
301 detail::convolve_2d(dx, sobel_y, dxdy);
302 detail::convolve_2d(dy, sobel_y, ddyy);
auto generate_dx_sobel(unsigned int degree=1) -> detail::kernel_2d< T, Allocator >
Generates Sobel operator in horizontal directionGenerates a kernel which will represent Sobel operato...
Definition: numeric.hpp:165
defined(BOOST_NO_CXX17_HDR_MEMORY_RESOURCE)
Definition: algorithm.hpp:36
auto generate_normalized_mean(std::size_t side_length) -> detail::kernel_2d< T, Allocator >
Generate mean kernelFills supplied view with normalized mean in which all entries will be equal to.
Definition: numeric.hpp:92
auto generate_dx_scharr(unsigned int degree=1) -> detail::kernel_2d< T, Allocator >
Generate Scharr operator in horizontal directionGenerates a kernel which will represent Scharr operat...
Definition: numeric.hpp:196
void compute_hessian_entries(GradientView dx, GradientView dy, OutputView ddxx, OutputView dxdy, OutputView ddyy)
Compute xy gradient, and second order x and y gradientsHessian matrix is defined as a matrix of parti...
Definition: numeric.hpp:291
double lanczos(double x, std::ptrdiff_t a)
Lanczos response at point xLanczos response is defined as: x == 0: 1 -a < x && x < a: 0 otherwise: no...
Definition: numeric.hpp:46
auto generate_unnormalized_mean(std::size_t side_length) -> detail::kernel_2d< T, Allocator >
Generate kernel with all 1sFills supplied view with 1s (ones)
Definition: numeric.hpp:112
auto generate_dy_sobel(unsigned int degree=1) -> detail::kernel_2d< T, Allocator >
Generates Sobel operator in vertical directionGenerates a kernel which will represent Sobel operator ...
Definition: numeric.hpp:227
auto generate_dy_scharr(unsigned int degree=1) -> detail::kernel_2d< T, Allocator >
Generate Scharr operator in vertical directionGenerates a kernel which will represent Scharr operator...
Definition: numeric.hpp:258
auto generate_gaussian_kernel(std::size_t side_length, double sigma) -> detail::kernel_2d< T, Allocator >
Generate Gaussian kernelFills supplied view with values taken from Gaussian distribution....
Definition: numeric.hpp:132
BOOST_FORCEINLINE auto copy(boost::gil::pixel< T, CS > *first, boost::gil::pixel< T, CS > *last, boost::gil::pixel< T, CS > *dst) -> boost::gil::pixel< T, CS > *
Copy when both src and dst are interleaved and of the same type can be just memmove.
Definition: algorithm.hpp:145
variable-size kernel
Definition: kernel.hpp:272