diff options
Diffstat (limited to 'third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c')
-rw-r--r-- | third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c | 171 |
1 files changed, 106 insertions, 65 deletions
diff --git a/third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c b/third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c index b3cb5bc5fd..bff7db6d2f 100644 --- a/third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c +++ b/third_party/aom/aom_dsp/flow_estimation/x86/corner_match_sse4.c @@ -21,84 +21,125 @@ #include "aom_ports/mem.h" #include "aom_dsp/flow_estimation/corner_match.h" -DECLARE_ALIGNED(16, static const uint8_t, - byte_mask[16]) = { 255, 255, 255, 255, 255, 255, 255, 255, - 255, 255, 255, 255, 255, 0, 0, 0 }; -#if MATCH_SZ != 13 -#error "Need to change byte_mask in corner_match_sse4.c if MATCH_SZ != 13" +DECLARE_ALIGNED(16, static const uint16_t, ones_array[8]) = { 1, 1, 1, 1, + 1, 1, 1, 1 }; + +#if MATCH_SZ != 16 +#error "Need to apply pixel mask in corner_match_sse4.c if MATCH_SZ != 16" #endif -/* Compute corr(frame1, frame2) * MATCH_SZ * stddev(frame1), where the - correlation/standard deviation are taken over MATCH_SZ by MATCH_SZ windows - of each image, centered at (x1, y1) and (x2, y2) respectively. +/* Compute mean and standard deviation of pixels in a window of size + MATCH_SZ by MATCH_SZ centered at (x, y). + Store results into *mean and *one_over_stddev + + Note: The output of this function is scaled by MATCH_SZ, as in + *mean = MATCH_SZ * <true mean> and + *one_over_stddev = 1 / (MATCH_SZ * <true stddev>) + + Combined with the fact that we return 1/stddev rather than the standard + deviation itself, this allows us to completely avoid divisions in + aom_compute_correlation, which is much hotter than this function is. + + Returns true if this feature point is usable, false otherwise. +*/ +bool aom_compute_mean_stddev_sse4_1(const unsigned char *frame, int stride, + int x, int y, double *mean, + double *one_over_stddev) { + // 8 16-bit partial sums of pixels + // Each lane sums at most 2*MATCH_SZ pixels, which can have values up to 255, + // and is therefore at most 2*MATCH_SZ*255, which is > 2^8 but < 2^16. + // Thus this value is safe to store in 16 bits. + __m128i sum_vec = _mm_setzero_si128(); + + // 8 32-bit partial sums of squares + __m128i sumsq_vec_l = _mm_setzero_si128(); + __m128i sumsq_vec_r = _mm_setzero_si128(); + + frame += (y - MATCH_SZ_BY2) * stride + (x - MATCH_SZ_BY2); + + for (int i = 0; i < MATCH_SZ; ++i) { + const __m128i v = _mm_loadu_si128((__m128i *)frame); + const __m128i v_l = _mm_cvtepu8_epi16(v); + const __m128i v_r = _mm_cvtepu8_epi16(_mm_srli_si128(v, 8)); + + sum_vec = _mm_add_epi16(sum_vec, _mm_add_epi16(v_l, v_r)); + sumsq_vec_l = _mm_add_epi32(sumsq_vec_l, _mm_madd_epi16(v_l, v_l)); + sumsq_vec_r = _mm_add_epi32(sumsq_vec_r, _mm_madd_epi16(v_r, v_r)); + + frame += stride; + } + + // Reduce sum_vec and sumsq_vec into single values + // Start by reducing each vector to 4x32-bit values, hadd() to perform four + // additions, then perform the last two additions in scalar code. + const __m128i ones = _mm_load_si128((__m128i *)ones_array); + const __m128i partial_sum = _mm_madd_epi16(sum_vec, ones); + const __m128i partial_sumsq = _mm_add_epi32(sumsq_vec_l, sumsq_vec_r); + const __m128i tmp = _mm_hadd_epi32(partial_sum, partial_sumsq); + const int sum = _mm_extract_epi32(tmp, 0) + _mm_extract_epi32(tmp, 1); + const int sumsq = _mm_extract_epi32(tmp, 2) + _mm_extract_epi32(tmp, 3); + + *mean = (double)sum / MATCH_SZ; + const double variance = sumsq - (*mean) * (*mean); + if (variance < MIN_FEATURE_VARIANCE) { + *one_over_stddev = 0.0; + return false; + } + *one_over_stddev = 1.0 / sqrt(variance); + return true; +} + +/* Compute corr(frame1, frame2) over a window of size MATCH_SZ by MATCH_SZ. + To save on computation, the mean and (1 divided by the) standard deviation + of the window in each frame are precomputed and passed into this function + as arguments. */ -double av1_compute_cross_correlation_sse4_1(const unsigned char *frame1, - int stride1, int x1, int y1, - const unsigned char *frame2, - int stride2, int x2, int y2) { - int i; - // 2 16-bit partial sums in lanes 0, 4 (== 2 32-bit partial sums in lanes 0, - // 2) - __m128i sum1_vec = _mm_setzero_si128(); - __m128i sum2_vec = _mm_setzero_si128(); - // 4 32-bit partial sums of squares - __m128i sumsq2_vec = _mm_setzero_si128(); - __m128i cross_vec = _mm_setzero_si128(); - - const __m128i mask = _mm_load_si128((__m128i *)byte_mask); - const __m128i zero = _mm_setzero_si128(); +double aom_compute_correlation_sse4_1(const unsigned char *frame1, int stride1, + int x1, int y1, double mean1, + double one_over_stddev1, + const unsigned char *frame2, int stride2, + int x2, int y2, double mean2, + double one_over_stddev2) { + // 8 32-bit partial sums of products + __m128i cross_vec_l = _mm_setzero_si128(); + __m128i cross_vec_r = _mm_setzero_si128(); frame1 += (y1 - MATCH_SZ_BY2) * stride1 + (x1 - MATCH_SZ_BY2); frame2 += (y2 - MATCH_SZ_BY2) * stride2 + (x2 - MATCH_SZ_BY2); - for (i = 0; i < MATCH_SZ; ++i) { - const __m128i v1 = - _mm_and_si128(_mm_loadu_si128((__m128i *)&frame1[i * stride1]), mask); - const __m128i v2 = - _mm_and_si128(_mm_loadu_si128((__m128i *)&frame2[i * stride2]), mask); - - // Using the 'sad' intrinsic here is a bit faster than adding - // v1_l + v1_r and v2_l + v2_r, plus it avoids the need for a 16->32 bit - // conversion step later, for a net speedup of ~10% - sum1_vec = _mm_add_epi16(sum1_vec, _mm_sad_epu8(v1, zero)); - sum2_vec = _mm_add_epi16(sum2_vec, _mm_sad_epu8(v2, zero)); + for (int i = 0; i < MATCH_SZ; ++i) { + const __m128i v1 = _mm_loadu_si128((__m128i *)frame1); + const __m128i v2 = _mm_loadu_si128((__m128i *)frame2); const __m128i v1_l = _mm_cvtepu8_epi16(v1); const __m128i v1_r = _mm_cvtepu8_epi16(_mm_srli_si128(v1, 8)); const __m128i v2_l = _mm_cvtepu8_epi16(v2); const __m128i v2_r = _mm_cvtepu8_epi16(_mm_srli_si128(v2, 8)); - sumsq2_vec = _mm_add_epi32( - sumsq2_vec, - _mm_add_epi32(_mm_madd_epi16(v2_l, v2_l), _mm_madd_epi16(v2_r, v2_r))); - cross_vec = _mm_add_epi32( - cross_vec, - _mm_add_epi32(_mm_madd_epi16(v1_l, v2_l), _mm_madd_epi16(v1_r, v2_r))); + cross_vec_l = _mm_add_epi32(cross_vec_l, _mm_madd_epi16(v1_l, v2_l)); + cross_vec_r = _mm_add_epi32(cross_vec_r, _mm_madd_epi16(v1_r, v2_r)); + + frame1 += stride1; + frame2 += stride2; } - // Now we can treat the four registers (sum1_vec, sum2_vec, sumsq2_vec, - // cross_vec) - // as holding 4 32-bit elements each, which we want to sum horizontally. - // We do this by transposing and then summing vertically. - __m128i tmp_0 = _mm_unpacklo_epi32(sum1_vec, sum2_vec); - __m128i tmp_1 = _mm_unpackhi_epi32(sum1_vec, sum2_vec); - __m128i tmp_2 = _mm_unpacklo_epi32(sumsq2_vec, cross_vec); - __m128i tmp_3 = _mm_unpackhi_epi32(sumsq2_vec, cross_vec); - - __m128i tmp_4 = _mm_unpacklo_epi64(tmp_0, tmp_2); - __m128i tmp_5 = _mm_unpackhi_epi64(tmp_0, tmp_2); - __m128i tmp_6 = _mm_unpacklo_epi64(tmp_1, tmp_3); - __m128i tmp_7 = _mm_unpackhi_epi64(tmp_1, tmp_3); - - __m128i res = - _mm_add_epi32(_mm_add_epi32(tmp_4, tmp_5), _mm_add_epi32(tmp_6, tmp_7)); - - int sum1 = _mm_extract_epi32(res, 0); - int sum2 = _mm_extract_epi32(res, 1); - int sumsq2 = _mm_extract_epi32(res, 2); - int cross = _mm_extract_epi32(res, 3); - - int var2 = sumsq2 * MATCH_SZ_SQ - sum2 * sum2; - int cov = cross * MATCH_SZ_SQ - sum1 * sum2; - return cov / sqrt((double)var2); + // Sum cross_vec into a single value + const __m128i tmp = _mm_add_epi32(cross_vec_l, cross_vec_r); + const int cross = _mm_extract_epi32(tmp, 0) + _mm_extract_epi32(tmp, 1) + + _mm_extract_epi32(tmp, 2) + _mm_extract_epi32(tmp, 3); + + // Note: In theory, the calculations here "should" be + // covariance = cross / N^2 - mean1 * mean2 + // correlation = covariance / (stddev1 * stddev2). + // + // However, because of the scaling in aom_compute_mean_stddev, the + // lines below actually calculate + // covariance * N^2 = cross - (mean1 * N) * (mean2 * N) + // correlation = (covariance * N^2) / ((stddev1 * N) * (stddev2 * N)) + // + // ie. we have removed the need for a division, and still end up with the + // correct unscaled correlation (ie, in the range [-1, +1]) + const double covariance = cross - mean1 * mean2; + const double correlation = covariance * (one_over_stddev1 * one_over_stddev2); + return correlation; } |