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Merge pull request #13146 from terfendail:bilateral_nan

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pull/13214/head
Alexander Alekhin 6 years ago
parent 94d7c0f7f5 9ad1a84853
commit 605071e76f
6 changed files with 688 additions and 38 deletions
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  1. 5
      modules/core/include/opencv2/core/hal/intrin_avx.hpp
  2. 19
      modules/core/include/opencv2/core/hal/intrin_cpp.hpp
  3. 7
      modules/core/include/opencv2/core/hal/intrin_neon.hpp
  4. 5
      modules/core/include/opencv2/core/hal/intrin_sse.hpp
  5. 5
      modules/core/include/opencv2/core/hal/intrin_vsx.hpp
  6. 665
      modules/imgproc/src/bilateral_filter.cpp

5
modules/core/include/opencv2/core/hal/intrin_avx.hpp
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@ -905,6 +905,11 @@ OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_int64x4)
OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float32x8, ps)
OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float64x4, pd)
inline v_float32x8 v_not_nan(const v_float32x8& a)
{ return v_float32x8(_mm256_cmp_ps(a.val, a.val, _CMP_ORD_Q)); }
inline v_float64x4 v_not_nan(const v_float64x4& a)
{ return v_float64x4(_mm256_cmp_pd(a.val, a.val, _CMP_ORD_Q)); }
/** min/max **/
OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint8x32, _mm256_min_epu8)
OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint8x32, _mm256_max_epu8)

19
modules/core/include/opencv2/core/hal/intrin_cpp.hpp
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@ -683,6 +683,25 @@ OPENCV_HAL_IMPL_CMP_OP(==)
For all types except 64-bit integer values. */
OPENCV_HAL_IMPL_CMP_OP(!=)
template<int n>
inline v_reg<float, n> v_not_nan(const v_reg<float, n>& a)
{
typedef typename V_TypeTraits<float>::int_type itype;
v_reg<float, n> c;
for (int i = 0; i < n; i++)
c.s[i] = V_TypeTraits<float>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
return c;
}
template<int n>
inline v_reg<double, n> v_not_nan(const v_reg<double, n>& a)
{
typedef typename V_TypeTraits<double>::int_type itype;
v_reg<double, n> c;
for (int i = 0; i < n; i++)
c.s[i] = V_TypeTraits<double>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
return c;
}
//! @brief Helper macro
//! @ingroup core_hal_intrin_impl
#define OPENCV_HAL_IMPL_ARITHM_OP(func, bin_op, cast_op, _Tp2) \

7
modules/core/include/opencv2/core/hal/intrin_neon.hpp
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@ -764,6 +764,13 @@ OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int64x2, vreinterpretq_s64_u64, s64, u64)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float64x2, vreinterpretq_f64_u64, f64, u64)
#endif
inline v_float32x4 v_not_nan(const v_float32x4& a)
{ return v_float32x4(vreinterpretq_f32_u32(vceqq_f32(a.val, a.val))); }
#if CV_SIMD128_64F
inline v_float64x2 v_not_nan(const v_float64x2& a)
{ return v_float64x2(vreinterpretq_f64_u64(vceqq_f64(a.val, a.val))); }
#endif
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_add_wrap, vaddq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_add_wrap, vaddq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_add_wrap, vaddq_u16)

5
modules/core/include/opencv2/core/hal/intrin_sse.hpp
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@ -1041,6 +1041,11 @@ inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \
OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_uint64x2, v_reinterpret_as_u64)
OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_int64x2, v_reinterpret_as_s64)
inline v_float32x4 v_not_nan(const v_float32x4& a)
{ return v_float32x4(_mm_cmpord_ps(a.val, a.val)); }
inline v_float64x2 v_not_nan(const v_float64x2& a)
{ return v_float64x2(_mm_cmpord_pd(a.val, a.val)); }
OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_add_wrap, _mm_add_epi8)
OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_add_wrap, _mm_add_epi8)
OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_add_wrap, _mm_add_epi16)

5
modules/core/include/opencv2/core/hal/intrin_vsx.hpp
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@ -607,6 +607,11 @@ OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float64x2)
OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint64x2)
OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int64x2)
inline v_float32x4 v_not_nan(const v_float32x4& a)
{ return v_float32x4(vec_cmpeq(a.val, a.val)); }
inline v_float64x2 v_not_nan(const v_float64x2& a)
{ return v_float64x2(vec_cmpeq(a.val, a.val)); }
/** min/max **/
OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_min, vec_min)
OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_max, vec_max)

665
modules/imgproc/src/bilateral_filter.cpp
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@ -82,7 +82,84 @@ public:
memset(buf.data(), 0, buf.size() * sizeof(float));
float *sum = alignPtr(buf.data(), CV_SIMD_WIDTH);
float *wsum = sum + alignSize(size.width, CV_SIMD_WIDTH);
for( k = 0; k < maxk; k++ )
k = 0;
for(; k <= maxk-4; k+=4)
{
const uchar* ksptr0 = sptr + space_ofs[k];
const uchar* ksptr1 = sptr + space_ofs[k+1];
const uchar* ksptr2 = sptr + space_ofs[k+2];
const uchar* ksptr3 = sptr + space_ofs[k+3];
j = 0;
#if CV_SIMD
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
{
v_uint32 rval = vx_load_expand_q(sptr + j);
v_uint32 val = vx_load_expand_q(ksptr0 + j);
v_float32 w = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
v_float32 v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, vx_load_aligned(sum + j));
val = vx_load_expand_q(ksptr1 + j);
w = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
v_wsum += w;
v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
val = vx_load_expand_q(ksptr2 + j);
w = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
v_wsum += w;
v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
val = vx_load_expand_q(ksptr3 + j);
w = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
v_wsum += w;
v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
v_store_aligned(wsum + j, v_wsum);
v_store_aligned(sum + j, v_sum);
}
#endif
#if CV_SIMD128
v_float32x4 kweight4 = v_load(space_weight + k);
#endif
for (; j < size.width; j++)
{
#if CV_SIMD128
v_uint32x4 rval = v_setall_u32(sptr[j]);
v_uint32x4 val(ksptr0[j], ksptr1[j], ksptr2[j], ksptr3[j]);
v_float32x4 w = kweight4 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
wsum[j] += v_reduce_sum(w);
sum[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(val)) * w);
#else
int rval = sptr[j];
int val = ksptr0[j];
float w = space_weight[k] * color_weight[std::abs(val - rval)];
wsum[j] += w;
sum[j] += val * w;
val = ksptr1[j];
w = space_weight[k+1] * color_weight[std::abs(val - rval)];
wsum[j] += w;
sum[j] += val * w;
val = ksptr2[j];
w = space_weight[k+2] * color_weight[std::abs(val - rval)];
wsum[j] += w;
sum[j] += val * w;
val = ksptr3[j];
w = space_weight[k+3] * color_weight[std::abs(val - rval)];
wsum[j] += w;
sum[j] += val * w;
#endif
}
}
for(; k < maxk; k++)
{
const uchar* ksptr = sptr + space_ofs[k];
j = 0;
@ -126,7 +203,232 @@ public:
float *sum_g = sum_b + alignSize(size.width, CV_SIMD_WIDTH);
float *sum_r = sum_g + alignSize(size.width, CV_SIMD_WIDTH);
float *wsum = sum_r + alignSize(size.width, CV_SIMD_WIDTH);
for(k = 0; k < maxk; k++ )
k = 0;
for(; k <= maxk-4; k+=4)
{
const uchar* ksptr0 = sptr + space_ofs[k];
const uchar* ksptr1 = sptr + space_ofs[k+1];
const uchar* ksptr2 = sptr + space_ofs[k+2];
const uchar* ksptr3 = sptr + space_ofs[k+3];
const uchar* rsptr = sptr;
j = 0;
#if CV_SIMD
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
for (; j <= size.width - v_uint8::nlanes; j += v_uint8::nlanes, rsptr += 3*v_uint8::nlanes,
ksptr0 += 3*v_uint8::nlanes, ksptr1 += 3*v_uint8::nlanes, ksptr2 += 3*v_uint8::nlanes, ksptr3 += 3*v_uint8::nlanes)
{
v_uint8 kb, kg, kr, rb, rg, rr;
v_load_deinterleave(rsptr, rb, rg, rr);
v_load_deinterleave(ksptr0, kb, kg, kr);
v_uint16 val0, val1, val2, val3, val4;
v_expand(v_absdiff(kb, rb), val0, val1);
v_expand(v_absdiff(kg, rg), val2, val3);
val0 += val2; val1 += val3;
v_expand(v_absdiff(kr, rr), val2, val3);
val0 += val2; val1 += val3;
v_uint32 vall, valh;
v_expand(val0, vall, valh);
v_float32 w0 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(vall));
v_float32 w1 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
v_expand(kb, val0, val2);
v_expand(val0, vall, valh);
v_store_aligned(sum_b + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
v_expand(kg, val0, val3);
v_expand(val0, vall, valh);
v_store_aligned(sum_g + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
v_expand(kr, val0, val4);
v_expand(val0, vall, valh);
v_store_aligned(sum_r + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
v_expand(val1, vall, valh);
w0 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
v_expand(val2, vall, valh);
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
v_expand(val3, vall, valh);
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
v_expand(val4, vall, valh);
v_store_aligned(sum_r + j + 2*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2*v_float32::nlanes)));
v_store_aligned(sum_r + j + 3*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3*v_float32::nlanes)));
v_load_deinterleave(ksptr1, kb, kg, kr);
v_expand(v_absdiff(kb, rb), val0, val1);
v_expand(v_absdiff(kg, rg), val2, val3);
val0 += val2; val1 += val3;
v_expand(v_absdiff(kr, rr), val2, val3);
val0 += val2; val1 += val3;
v_expand(val0, vall, valh);
w0 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
v_expand(kb, val0, val2);
v_expand(val0, vall, valh);
v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
v_expand(kg, val0, val3);
v_expand(val0, vall, valh);
v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
v_expand(kr, val0, val4);
v_expand(val0, vall, valh);
v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
v_expand(val1, vall, valh);
w0 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
v_expand(val2, vall, valh);
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
v_expand(val3, vall, valh);
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
v_expand(val4, vall, valh);
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
v_load_deinterleave(ksptr2, kb, kg, kr);
v_expand(v_absdiff(kb, rb), val0, val1);
v_expand(v_absdiff(kg, rg), val2, val3);
val0 += val2; val1 += val3;
v_expand(v_absdiff(kr, rr), val2, val3);
val0 += val2; val1 += val3;
v_expand(val0, vall, valh);
w0 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
v_expand(kb, val0, val2);
v_expand(val0, vall, valh);
v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
v_expand(kg, val0, val3);
v_expand(val0, vall, valh);
v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
v_expand(kr, val0, val4);
v_expand(val0, vall, valh);
v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
v_expand(val1, vall, valh);
w0 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
v_expand(val2, vall, valh);
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
v_expand(val3, vall, valh);
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
v_expand(val4, vall, valh);
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
v_load_deinterleave(ksptr3, kb, kg, kr);
v_expand(v_absdiff(kb, rb), val0, val1);
v_expand(v_absdiff(kg, rg), val2, val3);
val0 += val2; val1 += val3;
v_expand(v_absdiff(kr, rr), val2, val3);
val0 += val2; val1 += val3;
v_expand(val0, vall, valh);
w0 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
v_expand(kb, val0, val2);
v_expand(val0, vall, valh);
v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
v_expand(kg, val0, val3);
v_expand(val0, vall, valh);
v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
v_expand(kr, val0, val4);
v_expand(val0, vall, valh);
v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
v_expand(val1, vall, valh);
w0 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(vall));
w1 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(valh));
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
v_expand(val2, vall, valh);
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
v_expand(val3, vall, valh);
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
v_expand(val4, vall, valh);
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
}
#endif
#if CV_SIMD128
v_float32x4 kweight4 = v_load(space_weight + k);
#endif
for(; j < size.width; j++, rsptr += 3, ksptr0 += 3, ksptr1 += 3, ksptr2 += 3, ksptr3 += 3)
{
#if CV_SIMD128
v_uint32x4 rb = v_setall_u32(rsptr[0]);
v_uint32x4 rg = v_setall_u32(rsptr[1]);
v_uint32x4 rr = v_setall_u32(rsptr[2]);
v_uint32x4 b(ksptr0[0], ksptr1[0], ksptr2[0], ksptr3[0]);
v_uint32x4 g(ksptr0[1], ksptr1[1], ksptr2[1], ksptr3[1]);
v_uint32x4 r(ksptr0[2], ksptr1[2], ksptr2[2], ksptr3[2]);
v_float32x4 w = kweight4 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(b, rb) + v_absdiff(g, rg) + v_absdiff(r, rr)));
wsum[j] += v_reduce_sum(w);
sum_b[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(b)) * w);
sum_g[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(g)) * w);
sum_r[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(r)) * w);
#else
int rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
int b = ksptr0[0], g = ksptr0[1], r = ksptr0[2];
float w = space_weight[k]*color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
wsum[j] += w;
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
b = ksptr1[0]; g = ksptr1[1]; r = ksptr1[2];
w = space_weight[k+1] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
wsum[j] += w;
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
b = ksptr2[0]; g = ksptr2[1]; r = ksptr2[2];
w = space_weight[k+2] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
wsum[j] += w;
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
b = ksptr3[0]; g = ksptr3[1]; r = ksptr3[2];
w = space_weight[k+3] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
wsum[j] += w;
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
#endif
}
}
for(; k < maxk; k++)
{
const uchar* ksptr = sptr + space_ofs[k];
const uchar* rsptr = sptr;
@ -421,7 +723,130 @@ public:
v_float32 v_one = vx_setall_f32(1.f);
v_float32 sindex = vx_setall_f32(scale_index);
#endif
for( k = 0; k < maxk; k++ )
k = 0;
for(; k <= maxk - 4; k+=4)
{
const float* ksptr0 = sptr + space_ofs[k];
const float* ksptr1 = sptr + space_ofs[k + 1];
const float* ksptr2 = sptr + space_ofs[k + 2];
const float* ksptr3 = sptr + space_ofs[k + 3];
j = 0;
#if CV_SIMD
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
{
v_float32 rval = vx_load(sptr + j);
v_float32 val = vx_load(ksptr0 + j);
v_float32 knan = v_not_nan(val);
v_float32 alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
v_int32 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32 w = (kweight0 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha))) & knan;
v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
v_float32 v_sum = v_muladd(val & knan, w, vx_load_aligned(sum + j));
val = vx_load(ksptr1 + j);
knan = v_not_nan(val);
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight1 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum = v_muladd(val & knan, w, v_sum);
val = vx_load(ksptr2 + j);
knan = v_not_nan(val);
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight2 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum = v_muladd(val & knan, w, v_sum);
val = vx_load(ksptr3 + j);
knan = v_not_nan(val);
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight3 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum = v_muladd(val & knan, w, v_sum);
v_store_aligned(wsum + j, v_wsum);
v_store_aligned(sum + j, v_sum);
}
#endif
#if CV_SIMD128
v_float32x4 v_one4 = v_setall_f32(1.f);
v_float32x4 sindex4 = v_setall_f32(scale_index);
v_float32x4 kweight4 = v_load(space_weight + k);
#endif
for (; j < size.width; j++)
{
#if CV_SIMD128
v_float32x4 rval = v_setall_f32(sptr[j]);
v_float32x4 val(ksptr0[j], ksptr1[j], ksptr2[j], ksptr3[j]);
v_float32x4 knan = v_not_nan(val);
v_float32x4 alpha = (v_absdiff(val, rval) * sindex4) & v_not_nan(rval) & knan;
v_int32x4 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32x4 w = (kweight4 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one4 - alpha))) & knan;
wsum[j] += v_reduce_sum(w);
sum[j] += v_reduce_sum((val & knan) * w);
#else
float rval = sptr[j];
float val = ksptr0[j];
float alpha = std::abs(val - rval) * scale_index;
int idx = cvFloor(alpha);
alpha -= idx;
if (!cvIsNaN(val))
{
float w = space_weight[k] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum[j] += val * w;
}
val = ksptr1[j];
alpha = std::abs(val - rval) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!cvIsNaN(val))
{
float w = space_weight[k+1] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum[j] += val * w;
}
val = ksptr2[j];
alpha = std::abs(val - rval) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!cvIsNaN(val))
{
float w = space_weight[k+2] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum[j] += val * w;
}
val = ksptr3[j];
alpha = std::abs(val - rval) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!cvIsNaN(val))
{
float w = space_weight[k+3] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum[j] += val * w;
}
#endif
}
}
for(; k < maxk; k++)
{
const float* ksptr = sptr + space_ofs[k];
j = 0;
@ -430,36 +855,44 @@ public:
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
{
v_float32 val = vx_load(ksptr + j);
v_float32 alpha = v_absdiff(val, vx_load(sptr + j)) * sindex;
v_float32 rval = vx_load(sptr + j);
v_float32 knan = v_not_nan(val);
v_float32 alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
v_int32 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32 w = kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha));
v_float32 w = (kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha))) & knan;
v_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
v_store_aligned(sum + j, v_muladd(val, w, vx_load_aligned(sum + j)));
v_store_aligned(sum + j, v_muladd(val & knan, w, vx_load_aligned(sum + j)));
}
#endif
for (; j < size.width; j++)
{
float val = ksptr[j];
float alpha = std::abs(val - sptr[j]) * scale_index;
float rval = sptr[j];
float alpha = std::abs(val - rval) * scale_index;
int idx = cvFloor(alpha);
alpha -= idx;
float w = space_weight[k] * (expLUT[idx] + alpha*(expLUT[idx+1] - expLUT[idx]));
if (!cvIsNaN(val))
{
float w = space_weight[k] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum[j] += val * w;
}
}
}
j = 0;
#if CV_SIMD
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
v_store(dptr + j, vx_load_aligned(sum + j) / vx_load_aligned(wsum + j));
{
v_float32 v_val = vx_load(sptr + j);
v_store(dptr + j, (vx_load_aligned(sum + j) + (v_val & v_not_nan(v_val))) / (vx_load_aligned(wsum + j) + (v_one & v_not_nan(v_val))));
}
#endif
for (; j < size.width; j++)
{
CV_DbgAssert(fabs(wsum[j]) > 0);
dptr[j] = sum[j] / wsum[j];
CV_DbgAssert(fabs(wsum[j]) >= 0);
dptr[j] = cvIsNaN(sptr[j]) ? sum[j] / wsum[j] : (sum[j] + sptr[j]) / (wsum[j] + 1.f);
}
}
else
@ -475,7 +908,162 @@ public:
v_float32 v_one = vx_setall_f32(1.f);
v_float32 sindex = vx_setall_f32(scale_index);
#endif
for (k = 0; k < maxk; k++)
k = 0;
for (; k <= maxk-4; k+=4)
{
const float* ksptr0 = sptr + space_ofs[k];
const float* ksptr1 = sptr + space_ofs[k+1];
const float* ksptr2 = sptr + space_ofs[k+2];
const float* ksptr3 = sptr + space_ofs[k+3];
const float* rsptr = sptr;
j = 0;
#if CV_SIMD
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, rsptr += 3 * v_float32::nlanes,
ksptr0 += 3 * v_float32::nlanes, ksptr1 += 3 * v_float32::nlanes, ksptr2 += 3 * v_float32::nlanes, ksptr3 += 3 * v_float32::nlanes)
{
v_float32 kb, kg, kr, rb, rg, rr;
v_load_deinterleave(rsptr, rb, rg, rr);
v_load_deinterleave(ksptr0, kb, kg, kr);
v_float32 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
v_float32 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
v_int32 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32 w = (kweight0 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
v_float32 v_sum_b = v_muladd(kb & knan, w, vx_load_aligned(sum_b + j));
v_float32 v_sum_g = v_muladd(kg & knan, w, vx_load_aligned(sum_g + j));
v_float32 v_sum_r = v_muladd(kr & knan, w, vx_load_aligned(sum_r + j));
v_load_deinterleave(ksptr1, kb, kg, kr);
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight1 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
v_load_deinterleave(ksptr2, kb, kg, kr);
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight2 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
v_load_deinterleave(ksptr3, kb, kg, kr);
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
w = (kweight3 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_wsum += w;
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
v_store_aligned(wsum + j, v_wsum);
v_store_aligned(sum_b + j, v_sum_b);
v_store_aligned(sum_g + j, v_sum_g);
v_store_aligned(sum_r + j, v_sum_r);
}
#endif
#if CV_SIMD128
v_float32x4 v_one4 = v_setall_f32(1.f);
v_float32x4 sindex4 = v_setall_f32(scale_index);
v_float32x4 kweight4 = v_load(space_weight + k);
#endif
for (; j < size.width; j++, rsptr += 3, ksptr0 += 3, ksptr1 += 3, ksptr2 += 3, ksptr3 += 3)
{
#if CV_SIMD128
v_float32x4 rb = v_setall_f32(rsptr[0]);
v_float32x4 rg = v_setall_f32(rsptr[1]);
v_float32x4 rr = v_setall_f32(rsptr[2]);
v_float32x4 kb(ksptr0[0], ksptr1[0], ksptr2[0], ksptr3[0]);
v_float32x4 kg(ksptr0[1], ksptr1[1], ksptr2[1], ksptr3[1]);
v_float32x4 kr(ksptr0[2], ksptr1[2], ksptr2[2], ksptr3[2]);
v_float32x4 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
v_float32x4 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex4) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
v_int32x4 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32x4 w = (kweight4 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one4 - alpha))) & knan;
wsum[j] += v_reduce_sum(w);
sum_b[j] += v_reduce_sum((kb & knan) * w);
sum_g[j] += v_reduce_sum((kg & knan) * w);
sum_r[j] += v_reduce_sum((kr & knan) * w);
#else
float rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
bool r_NAN = cvIsNaN(rb) || cvIsNaN(rg) || cvIsNaN(rr);
float b = ksptr0[0], g = ksptr0[1], r = ksptr0[2];
bool v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
float alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
int idx = cvFloor(alpha);
alpha -= idx;
if (!v_NAN)
{
float w = space_weight[k] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum_b[j] += b*w;
sum_g[j] += g*w;
sum_r[j] += r*w;
}
b = ksptr1[0]; g = ksptr1[1]; r = ksptr1[2];
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!v_NAN)
{
float w = space_weight[k+1] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum_b[j] += b*w;
sum_g[j] += g*w;
sum_r[j] += r*w;
}
b = ksptr2[0]; g = ksptr2[1]; r = ksptr2[2];
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!v_NAN)
{
float w = space_weight[k+2] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum_b[j] += b*w;
sum_g[j] += g*w;
sum_r[j] += r*w;
}
b = ksptr3[0]; g = ksptr3[1]; r = ksptr3[2];
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
idx = cvFloor(alpha);
alpha -= idx;
if (!v_NAN)
{
float w = space_weight[k+3] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum_b[j] += b*w;
sum_g[j] += g*w;
sum_r[j] += r*w;
}
#endif
}
}
for (; k < maxk; k++)
{
const float* ksptr = sptr + space_ofs[k];
const float* rsptr = sptr;
@ -488,46 +1076,69 @@ public:
v_load_deinterleave(ksptr, kb, kg, kr);
v_load_deinterleave(rsptr, rb, rg, rr);
v_float32 alpha = (v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex;
v_float32 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
v_float32 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
v_int32 idx = v_trunc(alpha);
alpha -= v_cvt_f32(idx);
v_float32 w = kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha));
v_float32 w = (kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
v_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
v_store_aligned(sum_b + j, v_muladd(kb, w, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_g + j, v_muladd(kg, w, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_r + j, v_muladd(kr, w, vx_load_aligned(sum_r + j)));
v_store_aligned(sum_b + j, v_muladd(kb & knan, w, vx_load_aligned(sum_b + j)));
v_store_aligned(sum_g + j, v_muladd(kg & knan, w, vx_load_aligned(sum_g + j)));
v_store_aligned(sum_r + j, v_muladd(kr & knan, w, vx_load_aligned(sum_r + j)));
}
#endif
for (; j < size.width; j++, ksptr += 3, rsptr += 3)
{
float b = ksptr[0], g = ksptr[1], r = ksptr[2];
float alpha = (std::abs(b - rsptr[0]) + std::abs(g - rsptr[1]) + std::abs(r - rsptr[2])) * scale_index;
bool v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
float rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
bool r_NAN = cvIsNaN(rb) || cvIsNaN(rg) || cvIsNaN(rr);
float alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
int idx = cvFloor(alpha);
alpha -= idx;
float w = space_weight[k] * (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx]));
if (!v_NAN)
{
float w = space_weight[k] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
wsum[j] += w;
sum_b[j] += b*w;
sum_g[j] += g*w;
sum_r[j] += r*w;
}
}
}
j = 0;
#if CV_SIMD
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, dptr += 3*v_float32::nlanes)
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, sptr += 3*v_float32::nlanes, dptr += 3*v_float32::nlanes)
{
v_float32 w = v_one / vx_load_aligned(wsum + j);
v_store_interleave(dptr, vx_load_aligned(sum_b + j) * w, vx_load_aligned(sum_g + j) * w, vx_load_aligned(sum_r + j) * w);
v_float32 b, g, r;
v_load_deinterleave(sptr, b, g, r);
v_float32 mask = v_not_nan(b) & v_not_nan(g) & v_not_nan(r);
v_float32 w = v_one / (vx_load_aligned(wsum + j) + (v_one & mask));
v_store_interleave(dptr, (vx_load_aligned(sum_b + j) + (b & mask)) * w, (vx_load_aligned(sum_g + j) + (g & mask)) * w, (vx_load_aligned(sum_r + j) + (r & mask)) * w);
}
#endif
for (; j < size.width; j++)
{
CV_DbgAssert(fabs(wsum[j]) > 0);
CV_DbgAssert(fabs(wsum[j]) >= 0);
float b = *(sptr++);
float g = *(sptr++);
float r = *(sptr++);
if (cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r))
{
wsum[j] = 1.f / wsum[j];
*(dptr++) = sum_b[j] * wsum[j];
*(dptr++) = sum_g[j] * wsum[j];
*(dptr++) = sum_r[j] * wsum[j];
}
else
{
wsum[j] = 1.f / (wsum[j] + 1.f);
*(dptr++) = (sum_b[j] + b) * wsum[j];
*(dptr++) = (sum_g[j] + g) * wsum[j];
*(dptr++) = (sum_r[j] + r) * wsum[j];
}
}
}
}
#if CV_SIMD
@ -585,9 +1196,7 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
// temporary copy of the image with borders for easy processing
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
minValSrc -= 5. * sigma_color;
patchNaNs( temp, minValSrc ); // this replacement of NaNs makes the assumption that depth values are nonnegative
// TODO: make replacement parameter avalible in the outside function interface
// allocate lookup tables
std::vector<float> _space_weight(d*d);
std::vector<int> _space_ofs(d*d);
@ -620,7 +1229,7 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
if( r > radius )
if( r > radius || ( i == 0 && j == 0 ) )
continue;
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
space_ofs[maxk++] = (int)(i*(temp.step/sizeof(float)) + j*cn);

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