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 /* * 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 "aom_dsp/aom_dsp_common.h" #include "aom_dsp/fft_common.h" static INLINE void simple_transpose(const float *A, float *B, int n) { for (int y = 0; y < n; y++) { for (int x = 0; x < n; x++) { B[y * n + x] = A[x * n + y]; } } } // The 1d transform is real to complex and packs the complex results in // a way to take advantage of conjugate symmetry (e.g., the n/2 + 1 real // components, followed by the n/2 - 1 imaginary components). After the // transform is done on the rows, the first n/2 + 1 columns are real, and // the remaining are the imaginary components. After the transform on the // columns, the region of [0, n/2]x[0, n/2] contains the real part of // fft of the real columns. The real part of the 2d fft also includes the // imaginary part of transformed imaginary columns. This function assembles // the correct outputs while putting the real and imaginary components // next to each other. static INLINE void unpack_2d_output(const float *col_fft, float *output, int n) { for (int y = 0; y <= n / 2; ++y) { const int y2 = y + n / 2; const int y_extra = y2 > n / 2 && y2 < n; for (int x = 0; x <= n / 2; ++x) { const int x2 = x + n / 2; const int x_extra = x2 > n / 2 && x2 < n; output[2 * (y * n + x)] = col_fft[y * n + x] - (x_extra && y_extra ? col_fft[y2 * n + x2] : 0); output[2 * (y * n + x) + 1] = (y_extra ? col_fft[y2 * n + x] : 0) + (x_extra ? col_fft[y * n + x2] : 0); if (y_extra) { output[2 * ((n - y) * n + x)] = col_fft[y * n + x] + (x_extra && y_extra ? col_fft[y2 * n + x2] : 0); output[2 * ((n - y) * n + x) + 1] = -(y_extra ? col_fft[y2 * n + x] : 0) + (x_extra ? col_fft[y * n + x2] : 0); } } } } void aom_fft_2d_gen(const float *input, float *temp, float *output, int n, aom_fft_1d_func_t tform, aom_fft_transpose_func_t transpose, aom_fft_unpack_func_t unpack, int vec_size) { for (int x = 0; x < n; x += vec_size) { tform(input + x, output + x, n); } transpose(output, temp, n); for (int x = 0; x < n; x += vec_size) { tform(temp + x, output + x, n); } transpose(output, temp, n); unpack(temp, output, n); } static INLINE void store_float(float *output, float input) { *output = input; } static INLINE float add_float(float a, float b) { return a + b; } static INLINE float sub_float(float a, float b) { return a - b; } static INLINE float mul_float(float a, float b) { return a * b; } GEN_FFT_2(void, float, float, float, *, store_float); GEN_FFT_4(void, float, float, float, *, store_float, (float), add_float, sub_float); GEN_FFT_8(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); GEN_FFT_16(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); GEN_FFT_32(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); void aom_fft2x2_float_c(const float *input, float *temp, float *output) { aom_fft_2d_gen(input, temp, output, 2, aom_fft1d_2_float, simple_transpose, unpack_2d_output, 1); } void aom_fft4x4_float_c(const float *input, float *temp, float *output) { aom_fft_2d_gen(input, temp, output, 4, aom_fft1d_4_float, simple_transpose, unpack_2d_output, 1); } void aom_fft8x8_float_c(const float *input, float *temp, float *output) { aom_fft_2d_gen(input, temp, output, 8, aom_fft1d_8_float, simple_transpose, unpack_2d_output, 1); } void aom_fft16x16_float_c(const float *input, float *temp, float *output) { aom_fft_2d_gen(input, temp, output, 16, aom_fft1d_16_float, simple_transpose, unpack_2d_output, 1); } void aom_fft32x32_float_c(const float *input, float *temp, float *output) { aom_fft_2d_gen(input, temp, output, 32, aom_fft1d_32_float, simple_transpose, unpack_2d_output, 1); } void aom_ifft_2d_gen(const float *input, float *temp, float *output, int n, aom_fft_1d_func_t fft_single, aom_fft_1d_func_t fft_multi, aom_fft_1d_func_t ifft_multi, aom_fft_transpose_func_t transpose, int vec_size) { // Column 0 and n/2 have conjugate symmetry, so we can directly do the ifft // and get real outputs. for (int y = 0; y <= n / 2; ++y) { output[y * n] = input[2 * y * n]; output[y * n + 1] = input[2 * (y * n + n / 2)]; } for (int y = n / 2 + 1; y < n; ++y) { output[y * n] = input[2 * (y - n / 2) * n + 1]; output[y * n + 1] = input[2 * ((y - n / 2) * n + n / 2) + 1]; } for (int i = 0; i < 2; i += vec_size) { ifft_multi(output + i, temp + i, n); } // For the other columns, since we don't have a full ifft for complex inputs // we have to split them into the real and imaginary counterparts. // Pack the real component, then the imaginary components. for (int y = 0; y < n; ++y) { for (int x = 1; x < n / 2; ++x) { output[y * n + (x + 1)] = input[2 * (y * n + x)]; } for (int x = 1; x < n / 2; ++x) { output[y * n + (x + n / 2)] = input[2 * (y * n + x) + 1]; } } for (int y = 2; y < vec_size; y++) { fft_single(output + y, temp + y, n); } // This is the part that can be sped up with SIMD for (int y = AOMMAX(2, vec_size); y < n; y += vec_size) { fft_multi(output + y, temp + y, n); } // Put the 0 and n/2 th results in the correct place. for (int x = 0; x < n; ++x) { output[x] = temp[x * n]; output[(n / 2) * n + x] = temp[x * n + 1]; } // This rearranges and transposes. for (int y = 1; y < n / 2; ++y) { // Fill in the real columns for (int x = 0; x <= n / 2; ++x) { output[x + y * n] = temp[(y + 1) + x * n] + ((x > 0 && x < n / 2) ? temp[(y + n / 2) + (x + n / 2) * n] : 0); } for (int x = n / 2 + 1; x < n; ++x) { output[x + y * n] = temp[(y + 1) + (n - x) * n] - temp[(y + n / 2) + ((n - x) + n / 2) * n]; } // Fill in the imag columns for (int x = 0; x <= n / 2; ++x) { output[x + (y + n / 2) * n] = temp[(y + n / 2) + x * n] - ((x > 0 && x < n / 2) ? temp[(y + 1) + (x + n / 2) * n] : 0); } for (int x = n / 2 + 1; x < n; ++x) { output[x + (y + n / 2) * n] = temp[(y + 1) + ((n - x) + n / 2) * n] + temp[(y + n / 2) + (n - x) * n]; } } for (int y = 0; y < n; y += vec_size) { ifft_multi(output + y, temp + y, n); } transpose(temp, output, n); } GEN_IFFT_2(void, float, float, float, *, store_float); GEN_IFFT_4(void, float, float, float, *, store_float, (float), add_float, sub_float); GEN_IFFT_8(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); GEN_IFFT_16(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); GEN_IFFT_32(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float); void aom_ifft2x2_float_c(const float *input, float *temp, float *output) { aom_ifft_2d_gen(input, temp, output, 2, aom_fft1d_2_float, aom_fft1d_2_float, aom_ifft1d_2_float, simple_transpose, 1); } void aom_ifft4x4_float_c(const float *input, float *temp, float *output) { aom_ifft_2d_gen(input, temp, output, 4, aom_fft1d_4_float, aom_fft1d_4_float, aom_ifft1d_4_float, simple_transpose, 1); } void aom_ifft8x8_float_c(const float *input, float *temp, float *output) { aom_ifft_2d_gen(input, temp, output, 8, aom_fft1d_8_float, aom_fft1d_8_float, aom_ifft1d_8_float, simple_transpose, 1); } void aom_ifft16x16_float_c(const float *input, float *temp, float *output) { aom_ifft_2d_gen(input, temp, output, 16, aom_fft1d_16_float, aom_fft1d_16_float, aom_ifft1d_16_float, simple_transpose, 1); } void aom_ifft32x32_float_c(const float *input, float *temp, float *output) { aom_ifft_2d_gen(input, temp, output, 32, aom_fft1d_32_float, aom_fft1d_32_float, aom_ifft1d_32_float, simple_transpose, 1); }