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Updated bilateralFilter implementations to use wide universal intrinsics

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pull/12965/head
Vitaly Tuzov 6 years ago
parent 8396ae6e4f
commit 28fd967148
2 changed files with 230 additions and 281 deletions
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  1. 19
      modules/core/include/opencv2/core/hal/intrin_avx.hpp
  2. 492
      modules/imgproc/src/smooth.cpp

19
modules/core/include/opencv2/core/hal/intrin_avx.hpp
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@ -1363,25 +1363,22 @@ inline v_float64x4 v_cvt_f64_high(const v_float32x8& a)
inline v_int32x8 v_lut(const int* tab, const v_int32x8& idxvec)
{
int CV_DECL_ALIGNED(32) idx[8];
v_store_aligned(idx, idxvec);
return v_int32x8(_mm256_setr_epi32(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]));
return v_int32x8(_mm256_i32gather_epi32(tab, idxvec.val, 4));
}
inline v_uint32x8 v_lut(const unsigned* tab, const v_int32x8& idxvec)
{
return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
}
inline v_float32x8 v_lut(const float* tab, const v_int32x8& idxvec)
{
int CV_DECL_ALIGNED(32) idx[8];
v_store_aligned(idx, idxvec);
return v_float32x8(_mm256_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]));
return v_float32x8(_mm256_i32gather_ps(tab, idxvec.val, 4));
}
inline v_float64x4 v_lut(const double* tab, const v_int32x8& idxvec)
{
int CV_DECL_ALIGNED(32) idx[8];
v_store_aligned(idx, idxvec);
return v_float64x4(_mm256_setr_pd(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
return v_float64x4(_mm256_i32gather_pd(tab, _mm256_castsi256_si128(idxvec.val), 8));
}
inline void v_lut_deinterleave(const float* tab, const v_int32x8& idxvec, v_float32x8& x, v_float32x8& y)

492
modules/imgproc/src/smooth.cpp
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@ -2527,10 +2527,6 @@ public:
{
int i, j, cn = dest->channels(), k;
Size size = dest->size();
#if CV_SIMD128
int CV_DECL_ALIGNED(16) buf[4];
bool haveSIMD128 = hasSIMD128();
#endif
for( i = range.start; i < range.end; i++ )
{
@ -2539,154 +2535,153 @@ public:
if( cn == 1 )
{
for( j = 0; j < size.width; j++ )
AutoBuffer<float> buf(alignSize(size.width, CV_SIMD_WIDTH) + size.width + CV_SIMD_WIDTH - 1);
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++ )
{
float sum = 0, wsum = 0;
int val0 = sptr[j];
k = 0;
#if CV_SIMD128
if( haveSIMD128 )
const uchar* ksptr = sptr + space_ofs[k];
j = 0;
#if CV_SIMD
v_float32 kweight = vx_setall_f32(space_weight[k]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
{
v_float32x4 _val0 = v_setall_f32(static_cast<float>(val0));
v_float32x4 vsumw = v_setzero_f32();
v_float32x4 vsumc = v_setzero_f32();
for( ; k <= maxk - 4; k += 4 )
{
v_float32x4 _valF = v_float32x4(sptr[j + space_ofs[k]],
sptr[j + space_ofs[k + 1]],
sptr[j + space_ofs[k + 2]],
sptr[j + space_ofs[k + 3]]);
v_float32x4 _val = v_abs(_valF - _val0);
v_store(buf, v_round(_val));
v_float32x4 _cw = v_float32x4(color_weight[buf[0]],
color_weight[buf[1]],
color_weight[buf[2]],
color_weight[buf[3]]);
v_float32x4 _sw = v_load(space_weight+k);
#if defined(_MSC_VER) && _MSC_VER == 1700/* MSVS 2012 */ && CV_AVX
// details: https://github.com/opencv/opencv/issues/11004
vsumw += _cw * _sw;
vsumc += _cw * _sw * _valF;
#else
v_float32x4 _w = _cw * _sw;
_cw = _w * _valF;
vsumw += _w;
vsumc += _cw;
#endif
}
float *bufFloat = (float*)buf;
v_float32x4 sum4 = v_reduce_sum4(vsumw, vsumc, vsumw, vsumc);
v_store(bufFloat, sum4);
sum += bufFloat[1];
wsum += bufFloat[0];
v_uint32 val = vx_load_expand_q(ksptr + j);
v_float32 w = kweight * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, vx_load_expand_q(sptr + j))));
v_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
v_store_aligned(sum + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, vx_load_aligned(sum + j)));
}
#endif
for( ; k < maxk; k++ )
for (; j < size.width; j++)
{
int val = sptr[j + space_ofs[k]];
float w = space_weight[k]*color_weight[std::abs(val - val0)];
sum += val*w;
wsum += w;
int val = ksptr[j];
float w = space_weight[k] * color_weight[std::abs(val - sptr[j])];
wsum[j] += w;
sum[j] += val * w;
}
}
j = 0;
#if CV_SIMD
for (; j <= size.width - 2*v_float32::nlanes; j += 2*v_float32::nlanes)
v_pack_u_store(dptr + j, v_pack(v_round(vx_load_aligned(sum + j ) / vx_load_aligned(wsum + j )),
v_round(vx_load_aligned(sum + j + v_float32::nlanes) / vx_load_aligned(wsum + j + v_float32::nlanes))));
#endif
for (; j < size.width; j++)
{
// overflow is not possible here => there is no need to use cv::saturate_cast
CV_DbgAssert(fabs(wsum) > 0);
dptr[j] = (uchar)cvRound(sum/wsum);
CV_DbgAssert(fabs(wsum[j]) > 0);
dptr[j] = (uchar)cvRound(sum[j]/wsum[j]);
}
}
else
{
assert( cn == 3 );
for( j = 0; j < size.width*3; j += 3 )
AutoBuffer<float> buf(alignSize(size.width, CV_SIMD_WIDTH)*3 + size.width + CV_SIMD_WIDTH - 1);
memset(buf.data(), 0, buf.size() * sizeof(float));
float *sum_b = alignPtr(buf.data(), CV_SIMD_WIDTH);
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++ )
{
float sum_b = 0, sum_g = 0, sum_r = 0, wsum = 0;
int b0 = sptr[j], g0 = sptr[j+1], r0 = sptr[j+2];
k = 0;
#if CV_SIMD128
if( haveSIMD128 )
const uchar* ksptr = sptr + space_ofs[k];
const uchar* rsptr = sptr;
j = 0;
#if CV_SIMD
v_float32 kweight = vx_setall_f32(space_weight[k]);
for (; j <= size.width - v_uint8::nlanes; j += v_uint8::nlanes, ksptr += 3*v_uint8::nlanes, rsptr += 3*v_uint8::nlanes)
{
v_float32x4 vsumw = v_setzero_f32();
v_float32x4 vsumb = v_setzero_f32();
v_float32x4 vsumg = v_setzero_f32();
v_float32x4 vsumr = v_setzero_f32();
const v_float32x4 _b0 = v_setall_f32(static_cast<float>(b0));
const v_float32x4 _g0 = v_setall_f32(static_cast<float>(g0));
const v_float32x4 _r0 = v_setall_f32(static_cast<float>(r0));
for( ; k <= maxk - 4; k += 4 )
{
const uchar* const sptr_k0 = sptr + j + space_ofs[k];
const uchar* const sptr_k1 = sptr + j + space_ofs[k+1];
const uchar* const sptr_k2 = sptr + j + space_ofs[k+2];
const uchar* const sptr_k3 = sptr + j + space_ofs[k+3];
v_float32x4 __b = v_cvt_f32(v_reinterpret_as_s32(v_load_expand_q(sptr_k0)));
v_float32x4 __g = v_cvt_f32(v_reinterpret_as_s32(v_load_expand_q(sptr_k1)));
v_float32x4 __r = v_cvt_f32(v_reinterpret_as_s32(v_load_expand_q(sptr_k2)));
v_float32x4 __z = v_cvt_f32(v_reinterpret_as_s32(v_load_expand_q(sptr_k3)));
v_float32x4 _b, _g, _r, _z;
v_transpose4x4(__b, __g, __r, __z, _b, _g, _r, _z);
v_float32x4 bt = v_abs(_b -_b0);
v_float32x4 gt = v_abs(_g -_g0);
v_float32x4 rt = v_abs(_r -_r0);
bt = rt + bt + gt;
v_store(buf, v_round(bt));
v_float32x4 _w = v_float32x4(color_weight[buf[0]],color_weight[buf[1]],
color_weight[buf[2]],color_weight[buf[3]]);
v_float32x4 _sw = v_load(space_weight+k);
#if defined(_MSC_VER) && _MSC_VER == 1700/* MSVS 2012 */ && CV_AVX
// details: https://github.com/opencv/opencv/issues/11004
vsumw += _w * _sw;
vsumb += _w * _sw * _b;
vsumg += _w * _sw * _g;
vsumr += _w * _sw * _r;
#else
_w *= _sw;
_b *= _w;
_g *= _w;
_r *= _w;
vsumw += _w;
vsumb += _b;
vsumg += _g;
vsumr += _r;
#endif
}
float *bufFloat = (float*)buf;
v_float32x4 sum4 = v_reduce_sum4(vsumw, vsumb, vsumg, vsumr);
v_store(bufFloat, sum4);
wsum += bufFloat[0];
sum_b += bufFloat[1];
sum_g += bufFloat[2];
sum_r += bufFloat[3];
v_uint8 kb, kg, kr, rb, rg, rr;
v_load_deinterleave(ksptr, kb, kg, kr);
v_load_deinterleave(rsptr, rb, rg, rr);
v_uint16 b_l, b_h, g_l, g_h, r_l, r_h;
v_expand(v_absdiff(kb, rb), b_l, b_h);
v_expand(v_absdiff(kg, rg), g_l, g_h);
v_expand(v_absdiff(kr, rr), r_l, r_h);
v_uint32 val0, val1, val2, val3;
v_expand(b_l + g_l + r_l, val0, val1);
v_expand(b_h + g_h + r_h, val2, val3);
v_expand(kb, b_l, b_h);
v_expand(kg, g_l, g_h);
v_expand(kr, r_l, r_h);
v_float32 w0 = kweight * v_lut(color_weight, v_reinterpret_as_s32(val0));
v_float32 w1 = kweight * v_lut(color_weight, v_reinterpret_as_s32(val1));
v_float32 w2 = kweight * v_lut(color_weight, v_reinterpret_as_s32(val2));
v_float32 w3 = kweight * v_lut(color_weight, v_reinterpret_as_s32(val3));
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_store_aligned(wsum + j + 2*v_float32::nlanes, w2 + vx_load_aligned(wsum + j + 2*v_float32::nlanes));
v_store_aligned(wsum + j + 3*v_float32::nlanes, w3 + vx_load_aligned(wsum + j + 3*v_float32::nlanes));
v_expand(b_l, val0, val1);
v_expand(b_h, val2, val3);
v_store_aligned(sum_b + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(val0)), 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(val1)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
v_store_aligned(sum_b + j + 2*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(val2)), w2, 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(val3)), w3, vx_load_aligned(sum_b + j + 3*v_float32::nlanes)));
v_expand(g_l, val0, val1);
v_expand(g_h, val2, val3);
v_store_aligned(sum_g + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(val0)), 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(val1)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
v_store_aligned(sum_g + j + 2*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(val2)), w2, 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(val3)), w3, vx_load_aligned(sum_g + j + 3*v_float32::nlanes)));
v_expand(r_l, val0, val1);
v_expand(r_h, val2, val3);
v_store_aligned(sum_r + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(val0)), 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(val1)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
v_store_aligned(sum_r + j + 2*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(val2)), w2, 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(val3)), w3, vx_load_aligned(sum_r + j + 3*v_float32::nlanes)));
}
#endif
for( ; k < maxk; k++ )
for(; j < size.width; j++, ksptr += 3, rsptr += 3)
{
const uchar* sptr_k = sptr + j + space_ofs[k];
int b = sptr_k[0], g = sptr_k[1], r = sptr_k[2];
float w = space_weight[k]*color_weight[std::abs(b - b0) +
std::abs(g - g0) + std::abs(r - r0)];
sum_b += b*w; sum_g += g*w; sum_r += r*w;
wsum += w;
int b = ksptr[0], g = ksptr[1], r = ksptr[2];
float w = space_weight[k]*color_weight[std::abs(b - rsptr[0]) + std::abs(g - rsptr[1]) + std::abs(r - rsptr[2])];
wsum[j] += w;
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
}
CV_DbgAssert(fabs(wsum) > 0);
wsum = 1.f/wsum;
b0 = cvRound(sum_b*wsum);
g0 = cvRound(sum_g*wsum);
r0 = cvRound(sum_r*wsum);
dptr[j] = (uchar)b0; dptr[j+1] = (uchar)g0; dptr[j+2] = (uchar)r0;
}
j = 0;
#if CV_SIMD
v_float32 v_one = vx_setall_f32(1.f);
for(; j <= size.width - v_uint8::nlanes; j += v_uint8::nlanes, dptr += 3*v_uint8::nlanes)
{
v_float32 w0 = v_one / vx_load_aligned(wsum + j);
v_float32 w1 = v_one / vx_load_aligned(wsum + j + v_float32::nlanes);
v_float32 w2 = v_one / vx_load_aligned(wsum + j + 2*v_float32::nlanes);
v_float32 w3 = v_one / vx_load_aligned(wsum + j + 3*v_float32::nlanes);
v_store_interleave(dptr, v_pack_u(v_pack(v_round(w0 * vx_load_aligned(sum_b + j)),
v_round(w1 * vx_load_aligned(sum_b + j + v_float32::nlanes))),
v_pack(v_round(w2 * vx_load_aligned(sum_b + j + 2*v_float32::nlanes)),
v_round(w3 * vx_load_aligned(sum_b + j + 3*v_float32::nlanes)))),
v_pack_u(v_pack(v_round(w0 * vx_load_aligned(sum_g + j)),
v_round(w1 * vx_load_aligned(sum_g + j + v_float32::nlanes))),
v_pack(v_round(w2 * vx_load_aligned(sum_g + j + 2*v_float32::nlanes)),
v_round(w3 * vx_load_aligned(sum_g + j + 3*v_float32::nlanes)))),
v_pack_u(v_pack(v_round(w0 * vx_load_aligned(sum_r + j)),
v_round(w1 * vx_load_aligned(sum_r + j + v_float32::nlanes))),
v_pack(v_round(w2 * vx_load_aligned(sum_r + j + 2*v_float32::nlanes)),
v_round(w3 * vx_load_aligned(sum_r + j + 3*v_float32::nlanes)))));
}
#endif
for(; j < size.width; j++)
{
CV_DbgAssert(fabs(wsum[j]) > 0);
wsum[j] = 1.f/wsum[j];
*(dptr++) = (uchar)cvRound(sum_b[j]*wsum[j]);
*(dptr++) = (uchar)cvRound(sum_g[j]*wsum[j]);
*(dptr++) = (uchar)cvRound(sum_r[j]*wsum[j]);
}
}
}
#if CV_SIMD
vx_cleanup();
#endif
}
private:
@ -2867,10 +2862,6 @@ public:
{
int i, j, k;
Size size = dest->size();
#if CV_SIMD128
int CV_DECL_ALIGNED(16) idxBuf[4];
bool haveSIMD128 = hasSIMD128();
#endif
for( i = range.start; i < range.end; i++ )
{
@ -2879,165 +2870,126 @@ public:
if( cn == 1 )
{
for( j = 0; j < size.width; j++ )
AutoBuffer<float> buf(alignSize(size.width, CV_SIMD_WIDTH) + size.width + CV_SIMD_WIDTH - 1);
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);
#if CV_SIMD
v_float32 v_one = vx_setall_f32(1.f);
v_float32 sindex = vx_setall_f32(scale_index);
#endif
for( k = 0; k < maxk; k++ )
{
float sum = 0, wsum = 0;
float val0 = sptr[j];
k = 0;
#if CV_SIMD128
if( haveSIMD128 )
const float* ksptr = sptr + space_ofs[k];
j = 0;
#if CV_SIMD
v_float32 kweight = vx_setall_f32(space_weight[k]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
{
v_float32x4 vecwsum = v_setzero_f32();
v_float32x4 vecvsum = v_setzero_f32();
const v_float32x4 _val0 = v_setall_f32(sptr[j]);
const v_float32x4 _scale_index = v_setall_f32(scale_index);
for (; k <= maxk - 4; k += 4)
{
v_float32x4 _sw = v_load(space_weight + k);
v_float32x4 _val = v_float32x4(sptr[j + space_ofs[k]],
sptr[j + space_ofs[k + 1]],
sptr[j + space_ofs[k + 2]],
sptr[j + space_ofs[k + 3]]);
v_float32x4 _alpha = v_abs(_val - _val0) * _scale_index;
v_int32x4 _idx = v_round(_alpha);
v_store(idxBuf, _idx);
_alpha -= v_cvt_f32(_idx);
v_float32x4 _explut = v_float32x4(expLUT[idxBuf[0]],
expLUT[idxBuf[1]],
expLUT[idxBuf[2]],
expLUT[idxBuf[3]]);
v_float32x4 _explut1 = v_float32x4(expLUT[idxBuf[0] + 1],
expLUT[idxBuf[1] + 1],
expLUT[idxBuf[2] + 1],
expLUT[idxBuf[3] + 1]);
v_float32x4 _w = _sw * (_explut + (_alpha * (_explut1 - _explut)));
_val *= _w;
vecwsum += _w;
vecvsum += _val;
}
float *bufFloat = (float*)idxBuf;
v_float32x4 sum4 = v_reduce_sum4(vecwsum, vecvsum, vecwsum, vecvsum);
v_store(bufFloat, sum4);
sum += bufFloat[1];
wsum += bufFloat[0];
v_float32 val = vx_load(ksptr + j);
v_float32 alpha = v_absdiff(val, vx_load(sptr + j)) * sindex;
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_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
v_store_aligned(sum + j, v_muladd(val, w, vx_load_aligned(sum + j)));
}
#endif
for( ; k < maxk; k++ )
for (; j < size.width; j++)
{
float val = sptr[j + space_ofs[k]];
float alpha = (float)(std::abs(val - val0)*scale_index);
float val = ksptr[j];
float alpha = std::abs(val - sptr[j]) * scale_index;
int idx = cvFloor(alpha);
alpha -= idx;
float w = space_weight[k]*(expLUT[idx] + alpha*(expLUT[idx+1] - expLUT[idx]));
sum += val*w;
wsum += w;
float w = space_weight[k] * (expLUT[idx] + alpha*(expLUT[idx+1] - expLUT[idx]));
wsum[j] += w;
sum[j] += val * w;
}
CV_DbgAssert(fabs(wsum) > 0);
dptr[j] = (float)(sum/wsum);
}
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));
#endif
for (; j < size.width; j++)
{
CV_DbgAssert(fabs(wsum[j]) > 0);
dptr[j] = sum[j] / wsum[j];
}
}
else
{
CV_Assert( cn == 3 );
for( j = 0; j < size.width*3; j += 3 )
AutoBuffer<float> buf(alignSize(size.width, CV_SIMD_WIDTH)*3 + size.width + CV_SIMD_WIDTH - 1);
memset(buf.data(), 0, buf.size() * sizeof(float));
float *sum_b = alignPtr(buf.data(), CV_SIMD_WIDTH);
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);
#if CV_SIMD
v_float32 v_one = vx_setall_f32(1.f);
v_float32 sindex = vx_setall_f32(scale_index);
#endif
for (k = 0; k < maxk; k++)
{
float sum_b = 0, sum_g = 0, sum_r = 0, wsum = 0;
float b0 = sptr[j], g0 = sptr[j+1], r0 = sptr[j+2];
k = 0;
#if CV_SIMD128
if( haveSIMD128 )
const float* ksptr = sptr + space_ofs[k];
const float* rsptr = sptr;
j = 0;
#if CV_SIMD
v_float32 kweight = vx_setall_f32(space_weight[k]);
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, ksptr += 3*v_float32::nlanes, rsptr += 3*v_float32::nlanes)
{
v_float32x4 sumw = v_setzero_f32();
v_float32x4 sumb = v_setzero_f32();
v_float32x4 sumg = v_setzero_f32();
v_float32x4 sumr = v_setzero_f32();
const v_float32x4 _b0 = v_setall_f32(b0);
const v_float32x4 _g0 = v_setall_f32(g0);
const v_float32x4 _r0 = v_setall_f32(r0);
const v_float32x4 _scale_index = v_setall_f32(scale_index);
for( ; k <= maxk-4; k += 4 )
{
v_float32x4 _sw = v_load(space_weight + k);
const float* const sptr_k0 = sptr + j + space_ofs[k];
const float* const sptr_k1 = sptr + j + space_ofs[k+1];
const float* const sptr_k2 = sptr + j + space_ofs[k+2];
const float* const sptr_k3 = sptr + j + space_ofs[k+3];
v_float32x4 _v0 = v_load(sptr_k0);
v_float32x4 _v1 = v_load(sptr_k1);
v_float32x4 _v2 = v_load(sptr_k2);
v_float32x4 _v3 = v_load(sptr_k3);
v_float32x4 _b, _g, _r, _dummy;
v_transpose4x4(_v0, _v1, _v2, _v3, _b, _g, _r, _dummy);
v_float32x4 _bt = v_abs(_b - _b0);
v_float32x4 _gt = v_abs(_g - _g0);
v_float32x4 _rt = v_abs(_r - _r0);
v_float32x4 _alpha = _scale_index * (_bt + _gt + _rt);
v_int32x4 _idx = v_round(_alpha);
v_store((int*)idxBuf, _idx);
_alpha -= v_cvt_f32(_idx);
v_float32x4 _explut = v_float32x4(expLUT[idxBuf[0]],
expLUT[idxBuf[1]],
expLUT[idxBuf[2]],
expLUT[idxBuf[3]]);
v_float32x4 _explut1 = v_float32x4(expLUT[idxBuf[0] + 1],
expLUT[idxBuf[1] + 1],
expLUT[idxBuf[2] + 1],
expLUT[idxBuf[3] + 1]);
v_float32x4 _w = _sw * (_explut + (_alpha * (_explut1 - _explut)));
_b *= _w;
_g *= _w;
_r *= _w;
sumw += _w;
sumb += _b;
sumg += _g;
sumr += _r;
}
v_float32x4 sum4 = v_reduce_sum4(sumw, sumb, sumg, sumr);
float *bufFloat = (float*)idxBuf;
v_store(bufFloat, sum4);
wsum += bufFloat[0];
sum_b += bufFloat[1];
sum_g += bufFloat[2];
sum_r += bufFloat[3];
v_float32 kb, kg, kr, rb, rg, rr;
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_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_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)));
}
#endif
for(; k < maxk; k++ )
for (; j < size.width; j++, ksptr += 3, rsptr += 3)
{
const float* sptr_k = sptr + j + space_ofs[k];
float b = sptr_k[0], g = sptr_k[1], r = sptr_k[2];
float alpha = (float)((std::abs(b - b0) +
std::abs(g - g0) + std::abs(r - r0))*scale_index);
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;
int idx = cvFloor(alpha);
alpha -= idx;
float w = space_weight[k]*(expLUT[idx] + alpha*(expLUT[idx+1] - expLUT[idx]));
sum_b += b*w; sum_g += g*w; sum_r += r*w;
wsum += w;
float w = space_weight[k] * (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;
}
CV_DbgAssert(fabs(wsum) > 0);
wsum = 1.f/wsum;
b0 = sum_b*wsum;
g0 = sum_g*wsum;
r0 = sum_r*wsum;
dptr[j] = b0; dptr[j+1] = g0; dptr[j+2] = r0;
}
j = 0;
#if CV_SIMD
for (; j <= size.width - v_float32::nlanes; j += 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);
}
#endif
for (; j < size.width; j++)
{
CV_DbgAssert(fabs(wsum[j]) > 0);
wsum[j] = 1.f / wsum[j];
*(dptr++) = sum_b[j] * wsum[j];
*(dptr++) = sum_g[j] * wsum[j];
*(dptr++) = sum_r[j] * wsum[j];
}
}
}
#if CV_SIMD
vx_cleanup();
#endif
}
private:

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