[Olena-patches] olena: olena-2.0-591-ga674962 Add upscaled first octave

--- milena/sandbox/anthony/src/scale_space.cc | 191 ++++++++++++++++++++++++++--- 1 files changed, 174 insertions(+), 17 deletions(-) diff --git a/milena/sandbox/anthony/src/scale_space.cc b/milena/sandbox/anthony/src/scale_space.cc index 735d3f1..87853ef 100644 --- a/milena/sandbox/anthony/src/scale_space.cc +++ b/milena/sandbox/anthony/src/scale_space.cc @@ -11,19 +11,19 @@ using namespace mln; // Set the gaussian kernel -double *gaussian_kernel() +float *gaussian_kernel() { - double variance = sqrt(2.0); + float variance = sqrt(2.0); unsigned index = 0; - double *kernel = new double[49]; - static const double pi = 4.0 * atan(1.0); - double div = (2.0 * pi * variance); + float *kernel = new float[49]; + static const float pi = 4.0 * atan(1.0); + float div = (2.0 * pi * variance); for (int i = -3; i < 4; ++i) { for (int j = -3; j < 4; ++j) { - double e = exp(- (i*i + j*j) / (2.0 * variance) ); + float e = exp(- (i*i + j*j) / (2.0 * variance) ); kernel[index++] = e / div; } } @@ -33,7 +33,7 @@ double *gaussian_kernel() // Apply the convolution of the image by the kernel template<typename I> -void convolve(const I& original, I& filtered, double *kernel) +void convolve(const I& original, I& filtered, float *kernel) { mln_piter(I) p(filtered.domain()); window2d win; @@ -68,7 +68,7 @@ template<typename I> I blur(const I& original) { I filtered; - double *kernel = gaussian_kernel(); + float *kernel = gaussian_kernel(); initialize(filtered, original); convolve(original, filtered, kernel); @@ -125,6 +125,160 @@ I downscaling2(const I& original) return reduced; } +float *upscalingTL_kernel() +{ + const static float one = 1.0 / 8.0; + const static float two = 2.0 / 8.0; + const static float three = 2.0 / 8.0; + const static float four = 3.0 / 8.0; + + float *kernel = new float[4]; + + kernel[0] = one; + kernel[1] = two; + kernel[2] = three; + kernel[3] = four; + + return kernel; +} + +float *upscalingTR_kernel() +{ + const static float one = 2.0 / 8.0; + const static float two = 1.0 / 8.0; + const static float three = 3.0 / 8.0; + const static float four = 2.0 / 8.0; + + float *kernel = new float[4]; + + kernel[0] = one; + kernel[1] = two; + kernel[2] = three; + kernel[3] = four; + + return kernel; +} + +float *upscalingBL_kernel() +{ + const static float one = 2.0 / 8.0; + const static float two = 3.0 / 8.0; + const static float three = 1.0 / 8.0; + const static float four = 2.0 / 8.0; + + float *kernel = new float[4]; + + kernel[0] = one; + kernel[1] = two; + kernel[2] = three; + kernel[3] = four; + + return kernel; +} + +float *upscalingBR_kernel() +{ + const static float one = 3.0 / 8.0; + const static float two = 2.0 / 8.0; + const static float three = 2.0 / 8.0; + const static float four = 1.0 / 8.0; + + float *kernel = new float[4]; + + kernel[0] = one; + kernel[1] = two; + kernel[2] = three; + kernel[3] = four; + + return kernel; +} + +template<typename I> +unsigned upscalePixel(const I& original, int i, int j, int type) +{ + float *kernel; + window2d win; + mln_psite(I) p(i, j); + float value = 0; + unsigned index = 0; + int iStart = 0; + int jStart = 0; + + if (type == 0) + { + kernel = upscalingTL_kernel(); + iStart = -1; + jStart = -1; + } + else if (type == 1) + { + kernel = upscalingTR_kernel(); + iStart = 0; + jStart = -1; + } + else if (type == 2) + { + kernel = upscalingBL_kernel(); + iStart = -1; + jStart = 0; + } + else + { + kernel = upscalingBR_kernel(); + iStart = 0; + jStart = 0; + } + + for (int ii = iStart; ii < iStart + 2; ++ii) + for (int jj = jStart; jj < jStart + 2; ++jj) + win.insert(ii, jj); + + mln_qiter(window2d) q(win, p); + + for_all(q) + { + if (original.has(q)) + { + value += original(q) * kernel[index]; + } + + ++index; + } + + return (static_cast<int>(value)); +} + +// Upscale by 2 the image resolution +template<typename I> +I upscaling2(const I& original) +{ + box2d size(original.nrows() * 2, original.ncols() * 2); + I upscaled(size); + + mln_piter(I) p(upscaled.domain()); + int index = 0; + + for_all(p) + { + int i = p.col(); + int j = p.row(); + + if (i % 2 == 0 && j % 2 == 0) // Top left + opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 0); + else if (i % 2 == 0) // Bottom left + opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 2); + else if (j % 2 == 0) // Top right + opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 1); + else // Bottom right + opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 3); + + ++index; + } + + + return upscaled; +} + // Build the n-th octave on b blur levels template<typename I> void buildOctave(const I& original, @@ -165,18 +319,22 @@ void buildScaleSpace(std::vector< std::vector<I> >& scaleSpace, { if (n > 2) { + // Upscaled octave + I upscaled = upscaling2(original); + buildOctave(upscaled, 0, b, scaleSpace); + // 1st octave buildOctave(original, 1, b, scaleSpace); // 2nd octave - I reduced = downscaling2(original); - buildOctave(reduced, 2, b, scaleSpace); + I downscaled = downscaling2(original); + buildOctave(downscaled, 2, b, scaleSpace); for (unsigned i = 3; i <= n; ++i) { // i-th octave - reduced = downscaling2(reduced); - buildOctave(reduced, i, b, scaleSpace); + downscaled = downscaling2(downscaled); + buildOctave(downscaled, i, b, scaleSpace); } } else @@ -279,9 +437,6 @@ void buildExtrema(C extrema, std::vector< std::vector<I> >& dogSpace) { extrema = data::convert(value::rgb8(), original); - //value::int_u8 min = 255; - //value::int_u8 max = 0; - //value::int_u8 center = 0; const unsigned blur_level = dogSpace.at(0).size(); @@ -316,7 +471,8 @@ void buildExtrema(C extrema, if (center < min) { - mln_psite(I) pOriginal(p.row() * pow(2, j), p.col() * pow(2, j)); + mln_psite(I) pOriginal(p.row() * pow(2, (j-1)), + p.col() * pow(2, (j-1))); extrema(pOriginal) = literal::red; } } @@ -326,7 +482,8 @@ void buildExtrema(C extrema, if (center > max) { - mln_psite(I) pOriginal(p.row() * pow(2, j), p.col() * pow(2, j)); + mln_psite(I) pOriginal(p.row() * pow(2, (j-1)), + p.col() * pow(2, (j-1))); extrema(pOriginal) = literal::red; } } -- 1.7.2.5