/* * Copyright (c) 2018, Alliance for Open Media. All rights reserved. * * This source code is subject to the terms of the BSD 2 Clause License and * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License * was not distributed with this source code in the LICENSE file, you can * obtain it at www.aomedia.org/license/software. If the Alliance for Open * Media Patent License 1.0 was not distributed with this source code in the * PATENTS file, you can obtain it at www.aomedia.org/license/patent. */ #include #include #include "aom_dsp/x86/synonyms.h" #include "config/av1_rtcd.h" #include "av1/encoder/rdopt.h" // Process horizontal and vertical correlations in a 4x4 block of pixels. // We actually use the 4x4 pixels to calculate correlations corresponding to // the top-left 3x3 pixels, so this function must be called with 1x1 overlap, // moving the window along/down by 3 pixels at a time. static inline void horver_correlation_4x4(const int16_t *diff, int stride, __m128i *xy_sum_32, __m128i *xz_sum_32, __m128i *x_sum_32, __m128i *x2_sum_32) { // Pixels in this 4x4 [ a b c d ] // are referred to as: [ e f g h ] // [ i j k l ] // [ m n o p ] const __m128i pixelsa = xx_loadu_2x64(&diff[0 * stride], &diff[2 * stride]); const __m128i pixelsb = xx_loadu_2x64(&diff[1 * stride], &diff[3 * stride]); // pixelsa = [d c b a l k j i] as i16 // pixelsb = [h g f e p o n m] as i16 const __m128i slli_a = _mm_slli_epi64(pixelsa, 16); const __m128i slli_b = _mm_slli_epi64(pixelsb, 16); // slli_a = [c b a 0 k j i 0] as i16 // slli_b = [g f e 0 o n m 0] as i16 const __m128i xy_madd_a = _mm_madd_epi16(pixelsa, slli_a); const __m128i xy_madd_b = _mm_madd_epi16(pixelsb, slli_b); // xy_madd_a = [bc+cd ab jk+kl ij] as i32 // xy_madd_b = [fg+gh ef no+op mn] as i32 const __m128i xy32 = _mm_hadd_epi32(xy_madd_b, xy_madd_a); // xy32 = [ab+bc+cd ij+jk+kl ef+fg+gh mn+no+op] as i32 *xy_sum_32 = _mm_add_epi32(*xy_sum_32, xy32); const __m128i xz_madd_a = _mm_madd_epi16(slli_a, slli_b); // xz_madd_a = [bf+cg ae jn+ko im] i32 const __m128i swap_b = _mm_srli_si128(slli_b, 8); // swap_b = [0 0 0 0 g f e 0] as i16 const __m128i xz_madd_b = _mm_madd_epi16(slli_a, swap_b); // xz_madd_b = [0 0 gk+fj ei] i32 const __m128i xz32 = _mm_hadd_epi32(xz_madd_b, xz_madd_a); // xz32 = [ae+bf+cg im+jn+ko 0 ei+fj+gk] i32 *xz_sum_32 = _mm_add_epi32(*xz_sum_32, xz32); // Now calculate the straight sums, x_sum += a+b+c+e+f+g+i+j+k // (sum up every element in slli_a and swap_b) const __m128i sum_slli_a = _mm_hadd_epi16(slli_a, slli_a); const __m128i sum_slli_a32 = _mm_cvtepi16_epi32(sum_slli_a); // sum_slli_a32 = [c+b a k+j i] as i32 const __m128i swap_b32 = _mm_cvtepi16_epi32(swap_b); // swap_b32 = [g f e 0] as i32 *x_sum_32 = _mm_add_epi32(*x_sum_32, sum_slli_a32); *x_sum_32 = _mm_add_epi32(*x_sum_32, swap_b32); // sum = [c+b+g a+f k+j+e i] as i32 // Also sum their squares const __m128i slli_a_2 = _mm_madd_epi16(slli_a, slli_a); const __m128i swap_b_2 = _mm_madd_epi16(swap_b, swap_b); // slli_a_2 = [c2+b2 a2 k2+j2 i2] // swap_b_2 = [0 0 g2+f2 e2] const __m128i sum2 = _mm_hadd_epi32(slli_a_2, swap_b_2); // sum2 = [0 g2+f2+e2 c2+b2+a2 k2+j2+i2] *x2_sum_32 = _mm_add_epi32(*x2_sum_32, sum2); } void av1_get_horver_correlation_full_sse4_1(const int16_t *diff, int stride, int width, int height, float *hcorr, float *vcorr) { // The following notation is used: // x - current pixel // y - right neighbour pixel // z - below neighbour pixel // w - down-right neighbour pixel int64_t xy_sum = 0, xz_sum = 0; int64_t x_sum = 0, x2_sum = 0; // Process horizontal and vertical correlations through the body in 4x4 // blocks. This excludes the final row and column and possibly one extra // column depending how 3 divides into width and height int32_t xy_tmp[4] = { 0 }, xz_tmp[4] = { 0 }; int32_t x_tmp[4] = { 0 }, x2_tmp[4] = { 0 }; __m128i xy_sum_32 = _mm_setzero_si128(); __m128i xz_sum_32 = _mm_setzero_si128(); __m128i x_sum_32 = _mm_setzero_si128(); __m128i x2_sum_32 = _mm_setzero_si128(); for (int i = 0; i <= height - 4; i += 3) { for (int j = 0; j <= width - 4; j += 3) { horver_correlation_4x4(&diff[i * stride + j], stride, &xy_sum_32, &xz_sum_32, &x_sum_32, &x2_sum_32); } xx_storeu_128(xy_tmp, xy_sum_32); xx_storeu_128(xz_tmp, xz_sum_32); xx_storeu_128(x_tmp, x_sum_32); xx_storeu_128(x2_tmp, x2_sum_32); xy_sum += (int64_t)xy_tmp[3] + xy_tmp[2] + xy_tmp[1]; xz_sum += (int64_t)xz_tmp[3] + xz_tmp[2] + xz_tmp[0]; x_sum += (int64_t)x_tmp[3] + x_tmp[2] + x_tmp[1] + x_tmp[0]; x2_sum += (int64_t)x2_tmp[2] + x2_tmp[1] + x2_tmp[0]; xy_sum_32 = _mm_setzero_si128(); xz_sum_32 = _mm_setzero_si128(); x_sum_32 = _mm_setzero_si128(); x2_sum_32 = _mm_setzero_si128(); } // x_sum now covers every pixel except the final 1-2 rows and 1-2 cols int64_t x_finalrow = 0, x_finalcol = 0, x2_finalrow = 0, x2_finalcol = 0; // Do we have 2 rows remaining or just the one? Note that width and height // are powers of 2, so each modulo 3 must be 1 or 2. if (height % 3 == 1) { // Just horiz corrs on the final row const int16_t x0 = diff[(height - 1) * stride]; x_sum += x0; x_finalrow += x0; x2_sum += x0 * x0; x2_finalrow += x0 * x0; for (int j = 0; j < width - 1; ++j) { const int16_t x = diff[(height - 1) * stride + j]; const int16_t y = diff[(height - 1) * stride + j + 1]; xy_sum += x * y; x_sum += y; x2_sum += y * y; x_finalrow += y; x2_finalrow += y * y; } } else { // Two rows remaining to do const int16_t x0 = diff[(height - 2) * stride]; const int16_t z0 = diff[(height - 1) * stride]; x_sum += x0 + z0; x2_sum += x0 * x0 + z0 * z0; x_finalrow += z0; x2_finalrow += z0 * z0; for (int j = 0; j < width - 1; ++j) { const int16_t x = diff[(height - 2) * stride + j]; const int16_t y = diff[(height - 2) * stride + j + 1]; const int16_t z = diff[(height - 1) * stride + j]; const int16_t w = diff[(height - 1) * stride + j + 1]; // Horizontal and vertical correlations for the penultimate row: xy_sum += x * y; xz_sum += x * z; // Now just horizontal correlations for the final row: xy_sum += z * w; x_sum += y + w; x2_sum += y * y + w * w; x_finalrow += w; x2_finalrow += w * w; } } // Do we have 2 columns remaining or just the one? if (width % 3 == 1) { // Just vert corrs on the final col const int16_t x0 = diff[width - 1]; x_sum += x0; x_finalcol += x0; x2_sum += x0 * x0; x2_finalcol += x0 * x0; for (int i = 0; i < height - 1; ++i) { const int16_t x = diff[i * stride + width - 1]; const int16_t z = diff[(i + 1) * stride + width - 1]; xz_sum += x * z; x_finalcol += z; x2_finalcol += z * z; // So the bottom-right elements don't get counted twice: if (i < height - (height % 3 == 1 ? 2 : 3)) { x_sum += z; x2_sum += z * z; } } } else { // Two cols remaining const int16_t x0 = diff[width - 2]; const int16_t y0 = diff[width - 1]; x_sum += x0 + y0; x2_sum += x0 * x0 + y0 * y0; x_finalcol += y0; x2_finalcol += y0 * y0; for (int i = 0; i < height - 1; ++i) { const int16_t x = diff[i * stride + width - 2]; const int16_t y = diff[i * stride + width - 1]; const int16_t z = diff[(i + 1) * stride + width - 2]; const int16_t w = diff[(i + 1) * stride + width - 1]; // Horizontal and vertical correlations for the penultimate col: // Skip these on the last iteration of this loop if we also had two // rows remaining, otherwise the final horizontal and vertical correlation // get erroneously processed twice if (i < height - 2 || height % 3 == 1) { xy_sum += x * y; xz_sum += x * z; } x_finalcol += w; x2_finalcol += w * w; // So the bottom-right elements don't get counted twice: if (i < height - (height % 3 == 1 ? 2 : 3)) { x_sum += z + w; x2_sum += z * z + w * w; } // Now just vertical correlations for the final column: xz_sum += y * w; } } // Calculate the simple sums and squared-sums int64_t x_firstrow = 0, x_firstcol = 0; int64_t x2_firstrow = 0, x2_firstcol = 0; for (int j = 0; j < width; ++j) { x_firstrow += diff[j]; x2_firstrow += diff[j] * diff[j]; } for (int i = 0; i < height; ++i) { x_firstcol += diff[i * stride]; x2_firstcol += diff[i * stride] * diff[i * stride]; } int64_t xhor_sum = x_sum - x_finalcol; int64_t xver_sum = x_sum - x_finalrow; int64_t y_sum = x_sum - x_firstcol; int64_t z_sum = x_sum - x_firstrow; int64_t x2hor_sum = x2_sum - x2_finalcol; int64_t x2ver_sum = x2_sum - x2_finalrow; int64_t y2_sum = x2_sum - x2_firstcol; int64_t z2_sum = x2_sum - x2_firstrow; const float num_hor = (float)(height * (width - 1)); const float num_ver = (float)((height - 1) * width); const float xhor_var_n = x2hor_sum - (xhor_sum * xhor_sum) / num_hor; const float xver_var_n = x2ver_sum - (xver_sum * xver_sum) / num_ver; const float y_var_n = y2_sum - (y_sum * y_sum) / num_hor; const float z_var_n = z2_sum - (z_sum * z_sum) / num_ver; const float xy_var_n = xy_sum - (xhor_sum * y_sum) / num_hor; const float xz_var_n = xz_sum - (xver_sum * z_sum) / num_ver; if (xhor_var_n > 0 && y_var_n > 0) { *hcorr = xy_var_n / sqrtf(xhor_var_n * y_var_n); *hcorr = *hcorr < 0 ? 0 : *hcorr; } else { *hcorr = 1.0; } if (xver_var_n > 0 && z_var_n > 0) { *vcorr = xz_var_n / sqrtf(xver_var_n * z_var_n); *vcorr = *vcorr < 0 ? 0 : *vcorr; } else { *vcorr = 1.0; } }