| /* | |
| * Copyright (c) 2024, 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. | |
| */ | |
| #ifndef AOM_AOM_DSP_FLOW_ESTIMATION_ARM_DISFLOW_NEON_H_ | |
| #define AOM_AOM_DSP_FLOW_ESTIMATION_ARM_DISFLOW_NEON_H_ | |
| #include "aom_dsp/flow_estimation/disflow.h" | |
| #include <arm_neon.h> | |
| #include <math.h> | |
| #include "aom_dsp/arm/mem_neon.h" | |
| #include "config/aom_config.h" | |
| #include "config/aom_dsp_rtcd.h" | |
| static inline void get_cubic_kernel_dbl(double x, double kernel[4]) { | |
| // Check that the fractional position is in range. | |
| // | |
| // Note: x is calculated from, e.g., `u_frac = u - floor(u)`. | |
| // Mathematically, this implies that 0 <= x < 1. However, in practice it is | |
| // possible to have x == 1 due to floating point rounding. This is fine, | |
| // and we still interpolate correctly if we allow x = 1. | |
| assert(0 <= x && x <= 1); | |
| double x2 = x * x; | |
| double x3 = x2 * x; | |
| kernel[0] = -0.5 * x + x2 - 0.5 * x3; | |
| kernel[1] = 1.0 - 2.5 * x2 + 1.5 * x3; | |
| kernel[2] = 0.5 * x + 2.0 * x2 - 1.5 * x3; | |
| kernel[3] = -0.5 * x2 + 0.5 * x3; | |
| } | |
| static inline void get_cubic_kernel_int(double x, int kernel[4]) { | |
| double kernel_dbl[4]; | |
| get_cubic_kernel_dbl(x, kernel_dbl); | |
| kernel[0] = (int)rint(kernel_dbl[0] * (1 << DISFLOW_INTERP_BITS)); | |
| kernel[1] = (int)rint(kernel_dbl[1] * (1 << DISFLOW_INTERP_BITS)); | |
| kernel[2] = (int)rint(kernel_dbl[2] * (1 << DISFLOW_INTERP_BITS)); | |
| kernel[3] = (int)rint(kernel_dbl[3] * (1 << DISFLOW_INTERP_BITS)); | |
| } | |
| static inline void sobel_filter_x(const uint8_t *src, int src_stride, | |
| int16_t *dst, int dst_stride) { | |
| int16_t tmp[DISFLOW_PATCH_SIZE * (DISFLOW_PATCH_SIZE + 2)]; | |
| // Horizontal filter, using kernel {1, 0, -1}. | |
| const uint8_t *src_start = src - 1 * src_stride - 1; | |
| for (int i = 0; i < DISFLOW_PATCH_SIZE + 2; i++) { | |
| uint8x16_t s = vld1q_u8(src_start + i * src_stride); | |
| uint8x8_t s0 = vget_low_u8(s); | |
| uint8x8_t s2 = vget_low_u8(vextq_u8(s, s, 2)); | |
| // Given that the kernel is {1, 0, -1} the convolution is a simple | |
| // subtraction. | |
| int16x8_t diff = vreinterpretq_s16_u16(vsubl_u8(s0, s2)); | |
| vst1q_s16(tmp + i * DISFLOW_PATCH_SIZE, diff); | |
| } | |
| // Vertical filter, using kernel {1, 2, 1}. | |
| // This kernel can be split into two 2-taps kernels of value {1, 1}. | |
| // That way we need only 3 add operations to perform the convolution, one of | |
| // which can be reused for the next line. | |
| int16x8_t s0 = vld1q_s16(tmp); | |
| int16x8_t s1 = vld1q_s16(tmp + DISFLOW_PATCH_SIZE); | |
| int16x8_t sum01 = vaddq_s16(s0, s1); | |
| for (int i = 0; i < DISFLOW_PATCH_SIZE; i++) { | |
| int16x8_t s2 = vld1q_s16(tmp + (i + 2) * DISFLOW_PATCH_SIZE); | |
| int16x8_t sum12 = vaddq_s16(s1, s2); | |
| int16x8_t sum = vaddq_s16(sum01, sum12); | |
| vst1q_s16(dst + i * dst_stride, sum); | |
| sum01 = sum12; | |
| s1 = s2; | |
| } | |
| } | |
| static inline void sobel_filter_y(const uint8_t *src, int src_stride, | |
| int16_t *dst, int dst_stride) { | |
| int16_t tmp[DISFLOW_PATCH_SIZE * (DISFLOW_PATCH_SIZE + 2)]; | |
| // Horizontal filter, using kernel {1, 2, 1}. | |
| // This kernel can be split into two 2-taps kernels of value {1, 1}. | |
| // That way we need only 3 add operations to perform the convolution. | |
| const uint8_t *src_start = src - 1 * src_stride - 1; | |
| for (int i = 0; i < DISFLOW_PATCH_SIZE + 2; i++) { | |
| uint8x16_t s = vld1q_u8(src_start + i * src_stride); | |
| uint8x8_t s0 = vget_low_u8(s); | |
| uint8x8_t s1 = vget_low_u8(vextq_u8(s, s, 1)); | |
| uint8x8_t s2 = vget_low_u8(vextq_u8(s, s, 2)); | |
| uint16x8_t sum01 = vaddl_u8(s0, s1); | |
| uint16x8_t sum12 = vaddl_u8(s1, s2); | |
| uint16x8_t sum = vaddq_u16(sum01, sum12); | |
| vst1q_s16(tmp + i * DISFLOW_PATCH_SIZE, vreinterpretq_s16_u16(sum)); | |
| } | |
| // Vertical filter, using kernel {1, 0, -1}. | |
| // Load the whole block at once to avoid redundant loads during convolution. | |
| int16x8_t t[10]; | |
| load_s16_8x10(tmp, DISFLOW_PATCH_SIZE, &t[0], &t[1], &t[2], &t[3], &t[4], | |
| &t[5], &t[6], &t[7], &t[8], &t[9]); | |
| for (int i = 0; i < DISFLOW_PATCH_SIZE; i++) { | |
| // Given that the kernel is {1, 0, -1} the convolution is a simple | |
| // subtraction. | |
| int16x8_t diff = vsubq_s16(t[i], t[i + 2]); | |
| vst1q_s16(dst + i * dst_stride, diff); | |
| } | |
| } | |
| #endif // AOM_AOM_DSP_FLOW_ESTIMATION_ARM_DISFLOW_NEON_H_ |