Warning fixes continued
This commit is contained in:
Andrey Kamaev
@@ -46,14 +46,14 @@
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Proceedings of the 5th International Symposium on Visual Computing, Vegas, USA
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This code is written by Sergey G. Kosov for "Visir PX" application as part of Project X (www.project-10.de)
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*/
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*/
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#include "precomp.hpp"
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#include <limits.h>
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namespace cv
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namespace cv
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{
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StereoVar::StereoVar() : levels(3), pyrScale(0.5), nIt(5), minDisp(0), maxDisp(16), poly_n(3), poly_sigma(0), fi(25.0f), lambda(0.03f), penalization(PENALIZATION_TICHONOV), cycle(CYCLE_V), flags(USE_SMART_ID | USE_AUTO_PARAMS)
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StereoVar::StereoVar() : levels(3), pyrScale(0.5), nIt(5), minDisp(0), maxDisp(16), poly_n(3), poly_sigma(0), fi(25.0f), lambda(0.03f), penalization(PENALIZATION_TICHONOV), cycle(CYCLE_V), flags(USE_SMART_ID | USE_AUTO_PARAMS)
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{
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}
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@@ -67,9 +67,9 @@ StereoVar::~StereoVar()
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static Mat diffX(Mat &src)
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{
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register int x, y, cols = src.cols - 1;
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Mat dst(src.size(), src.type());
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for(y = 0; y < src.rows; y++){
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register int x, y, cols = src.cols - 1;
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Mat dst(src.size(), src.type());
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for(y = 0; y < src.rows; y++){
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const float* pSrc = src.ptr<float>(y);
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float* pDst = dst.ptr<float>(y);
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#if CV_SSE2
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@@ -92,319 +92,319 @@ static Mat diffX(Mat &src)
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static Mat getGradient(Mat &src)
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{
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register int x, y;
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Mat dst(src.size(), src.type());
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dst.setTo(0);
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for (y = 0; y < src.rows - 1; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pSrcF = src.ptr<float>(y + 1);
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float *pDst = dst.ptr<float>(y);
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for (x = 0; x < src.cols - 1; x++)
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pDst[x] = fabs(pSrc[x + 1] - pSrc[x]) + fabs(pSrcF[x] - pSrc[x]);
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}
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return dst;
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register int x, y;
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Mat dst(src.size(), src.type());
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dst.setTo(0);
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for (y = 0; y < src.rows - 1; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pSrcF = src.ptr<float>(y + 1);
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float *pDst = dst.ptr<float>(y);
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for (x = 0; x < src.cols - 1; x++)
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pDst[x] = fabs(pSrc[x + 1] - pSrc[x]) + fabs(pSrcF[x] - pSrc[x]);
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}
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return dst;
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}
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static Mat getG_c(Mat &src, float l)
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{
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Mat dst(src.size(), src.type());
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for (register int y = 0; y < src.rows; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pDst = dst.ptr<float>(y);
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for (register int x = 0; x < src.cols; x++)
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pDst[x] = 0.5f*l / sqrtf(l*l + pSrc[x]*pSrc[x]);
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}
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return dst;
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Mat dst(src.size(), src.type());
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for (register int y = 0; y < src.rows; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pDst = dst.ptr<float>(y);
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for (register int x = 0; x < src.cols; x++)
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pDst[x] = 0.5f*l / sqrtf(l*l + pSrc[x]*pSrc[x]);
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}
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return dst;
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}
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static Mat getG_p(Mat &src, float l)
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{
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Mat dst(src.size(), src.type());
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for (register int y = 0; y < src.rows; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pDst = dst.ptr<float>(y);
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for (register int x = 0; x < src.cols; x++)
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pDst[x] = 0.5f*l*l / (l*l + pSrc[x]*pSrc[x]);
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}
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return dst;
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Mat dst(src.size(), src.type());
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for (register int y = 0; y < src.rows; y++) {
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float *pSrc = src.ptr<float>(y);
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float *pDst = dst.ptr<float>(y);
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for (register int x = 0; x < src.cols; x++)
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pDst[x] = 0.5f*l*l / (l*l + pSrc[x]*pSrc[x]);
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}
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return dst;
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}
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void StereoVar::VariationalSolver(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
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{
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register int n, x, y;
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float gl = 1, gr = 1, gu = 1, gd = 1, gc = 4;
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Mat g_c, g_p;
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Mat U;
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u.copyTo(U);
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register int n, x, y;
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float gl = 1, gr = 1, gu = 1, gd = 1, gc = 4;
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Mat g_c, g_p;
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Mat U;
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u.copyTo(U);
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int N = nIt;
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float l = lambda;
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float Fi = fi;
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int N = nIt;
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float l = lambda;
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float Fi = fi;
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if (flags & USE_SMART_ID) {
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double scale = pow(pyrScale, (double) level) * (1 + pyrScale);
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N = (int) (N / scale);
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}
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double scale = pow(pyrScale, (double) level);
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Fi /= (float) scale;
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l *= (float) scale;
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if (flags & USE_SMART_ID) {
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double scale = pow(pyrScale, (double) level) * (1 + pyrScale);
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N = (int) (N / scale);
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}
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int width = u.cols - 1;
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int height = u.rows - 1;
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for (n = 0; n < N; n++) {
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if (penalization != PENALIZATION_TICHONOV) {
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Mat gradient = getGradient(U);
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switch (penalization) {
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case PENALIZATION_CHARBONNIER: g_c = getG_c(gradient, l); break;
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case PENALIZATION_PERONA_MALIK: g_p = getG_p(gradient, l); break;
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}
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gradient.release();
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}
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for (y = 1 ; y < height; y++) {
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float *pU = U.ptr<float>(y);
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float *pUu = U.ptr<float>(y + 1);
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float *pUd = U.ptr<float>(y - 1);
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float *pu = u.ptr<float>(y);
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float *pI1 = I1.ptr<float>(y);
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float *pI2 = I2.ptr<float>(y);
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float *pI2x = I2x.ptr<float>(y);
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float *pG_c = NULL, *pG_cu = NULL, *pG_cd = NULL;
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float *pG_p = NULL, *pG_pu = NULL, *pG_pd = NULL;
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switch (penalization) {
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case PENALIZATION_CHARBONNIER:
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pG_c = g_c.ptr<float>(y);
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pG_cu = g_c.ptr<float>(y + 1);
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pG_cd = g_c.ptr<float>(y - 1);
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break;
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case PENALIZATION_PERONA_MALIK:
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pG_p = g_p.ptr<float>(y);
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pG_pu = g_p.ptr<float>(y + 1);
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pG_pd = g_p.ptr<float>(y - 1);
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break;
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}
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for (x = 1; x < width; x++) {
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switch (penalization) {
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case PENALIZATION_CHARBONNIER:
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gc = pG_c[x];
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gl = gc + pG_c[x - 1];
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gr = gc + pG_c[x + 1];
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gu = gc + pG_cu[x];
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gd = gc + pG_cd[x];
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gc = gl + gr + gu + gd;
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break;
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case PENALIZATION_PERONA_MALIK:
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gc = pG_p[x];
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gl = gc + pG_p[x - 1];
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gr = gc + pG_p[x + 1];
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gu = gc + pG_pu[x];
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gd = gc + pG_pd[x];
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gc = gl + gr + gu + gd;
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break;
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}
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double scale = pow(pyrScale, (double) level);
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Fi /= (float) scale;
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l *= (float) scale;
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float fi = Fi;
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if (maxDisp > minDisp) {
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if (pU[x] > maxDisp * scale) {fi *= 1000; pU[x] = static_cast<float>(maxDisp * scale);}
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if (pU[x] < minDisp * scale) {fi *= 1000; pU[x] = static_cast<float>(minDisp * scale);}
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}
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int width = u.cols - 1;
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int height = u.rows - 1;
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for (n = 0; n < N; n++) {
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if (penalization != PENALIZATION_TICHONOV) {
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Mat gradient = getGradient(U);
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switch (penalization) {
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case PENALIZATION_CHARBONNIER: g_c = getG_c(gradient, l); break;
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case PENALIZATION_PERONA_MALIK: g_p = getG_p(gradient, l); break;
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}
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gradient.release();
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}
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for (y = 1 ; y < height; y++) {
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float *pU = U.ptr<float>(y);
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float *pUu = U.ptr<float>(y + 1);
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float *pUd = U.ptr<float>(y - 1);
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float *pu = u.ptr<float>(y);
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float *pI1 = I1.ptr<float>(y);
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float *pI2 = I2.ptr<float>(y);
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float *pI2x = I2x.ptr<float>(y);
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float *pG_c = NULL, *pG_cu = NULL, *pG_cd = NULL;
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float *pG_p = NULL, *pG_pu = NULL, *pG_pd = NULL;
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switch (penalization) {
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case PENALIZATION_CHARBONNIER:
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pG_c = g_c.ptr<float>(y);
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pG_cu = g_c.ptr<float>(y + 1);
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pG_cd = g_c.ptr<float>(y - 1);
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break;
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case PENALIZATION_PERONA_MALIK:
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pG_p = g_p.ptr<float>(y);
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pG_pu = g_p.ptr<float>(y + 1);
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pG_pd = g_p.ptr<float>(y - 1);
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break;
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}
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for (x = 1; x < width; x++) {
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switch (penalization) {
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case PENALIZATION_CHARBONNIER:
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gc = pG_c[x];
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gl = gc + pG_c[x - 1];
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gr = gc + pG_c[x + 1];
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gu = gc + pG_cu[x];
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gd = gc + pG_cd[x];
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gc = gl + gr + gu + gd;
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break;
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case PENALIZATION_PERONA_MALIK:
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gc = pG_p[x];
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gl = gc + pG_p[x - 1];
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gr = gc + pG_p[x + 1];
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gu = gc + pG_pu[x];
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gd = gc + pG_pd[x];
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gc = gl + gr + gu + gd;
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break;
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}
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int A = static_cast<int>(pU[x]);
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int neg = 0; if (pU[x] <= 0) neg = -1;
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float _fi = Fi;
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if (maxDisp > minDisp) {
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if (pU[x] > maxDisp * scale) {_fi *= 1000; pU[x] = static_cast<float>(maxDisp * scale);}
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if (pU[x] < minDisp * scale) {_fi *= 1000; pU[x] = static_cast<float>(minDisp * scale);}
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}
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if (x + A > width)
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pu[x] = pU[width - A];
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else if (x + A + neg < 0)
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pu[x] = pU[- A + 2];
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else {
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pu[x] = A + (pI2x[x + A + neg] * (pI1[x] - pI2[x + A])
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+ fi * (gr * pU[x + 1] + gl * pU[x - 1] + gu * pUu[x] + gd * pUd[x] - gc * A))
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/ (pI2x[x + A + neg] * pI2x[x + A + neg] + gc * fi) ;
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}
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}// x
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pu[0] = pu[1];
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pu[width] = pu[width - 1];
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}// y
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for (x = 0; x <= width; x++) {
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u.at<float>(0, x) = u.at<float>(1, x);
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u.at<float>(height, x) = u.at<float>(height - 1, x);
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}
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u.copyTo(U);
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if (!g_c.empty()) g_c.release();
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if (!g_p.empty()) g_p.release();
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}//n
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int A = static_cast<int>(pU[x]);
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int neg = 0; if (pU[x] <= 0) neg = -1;
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if (x + A > width)
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pu[x] = pU[width - A];
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else if (x + A + neg < 0)
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pu[x] = pU[- A + 2];
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else {
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pu[x] = A + (pI2x[x + A + neg] * (pI1[x] - pI2[x + A])
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+ _fi * (gr * pU[x + 1] + gl * pU[x - 1] + gu * pUu[x] + gd * pUd[x] - gc * A))
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/ (pI2x[x + A + neg] * pI2x[x + A + neg] + gc * _fi) ;
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}
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}// x
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pu[0] = pu[1];
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pu[width] = pu[width - 1];
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}// y
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for (x = 0; x <= width; x++) {
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u.at<float>(0, x) = u.at<float>(1, x);
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u.at<float>(height, x) = u.at<float>(height - 1, x);
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}
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u.copyTo(U);
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if (!g_c.empty()) g_c.release();
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if (!g_p.empty()) g_p.release();
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}//n
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}
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void StereoVar::VCycle_MyFAS(Mat &I1, Mat &I2, Mat &I2x, Mat &_u, int level)
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{
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CvSize imgSize = _u.size();
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CvSize frmSize = cvSize((int) (imgSize.width * pyrScale + 0.5), (int) (imgSize.height * pyrScale + 0.5));
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Mat I1_h, I2_h, I2x_h, u_h, U, U_h;
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CvSize imgSize = _u.size();
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CvSize frmSize = cvSize((int) (imgSize.width * pyrScale + 0.5), (int) (imgSize.height * pyrScale + 0.5));
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Mat I1_h, I2_h, I2x_h, u_h, U, U_h;
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//PRE relaxation
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VariationalSolver(I1, I2, I2x, _u, level);
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//PRE relaxation
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VariationalSolver(I1, I2, I2x, _u, level);
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if (level >= levels - 1) return;
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level ++;
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if (level >= levels - 1) return;
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level ++;
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//scaling DOWN
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resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
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resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
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resize(_u, u_h, frmSize, 0, 0, INTER_AREA);
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u_h.convertTo(u_h, u_h.type(), pyrScale);
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I2x_h = diffX(I2_h);
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//scaling DOWN
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resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
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resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
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resize(_u, u_h, frmSize, 0, 0, INTER_AREA);
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u_h.convertTo(u_h, u_h.type(), pyrScale);
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I2x_h = diffX(I2_h);
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//Next level
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U_h = u_h.clone();
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VCycle_MyFAS(I1_h, I2_h, I2x_h, U_h, level);
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//Next level
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U_h = u_h.clone();
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VCycle_MyFAS(I1_h, I2_h, I2x_h, U_h, level);
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subtract(U_h, u_h, U_h);
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U_h.convertTo(U_h, U_h.type(), 1.0 / pyrScale);
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subtract(U_h, u_h, U_h);
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U_h.convertTo(U_h, U_h.type(), 1.0 / pyrScale);
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//scaling UP
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resize(U_h, U, imgSize);
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//scaling UP
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resize(U_h, U, imgSize);
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//correcting the solution
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add(_u, U, _u);
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//correcting the solution
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add(_u, U, _u);
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//POST relaxation
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VariationalSolver(I1, I2, I2x, _u, level - 1);
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//POST relaxation
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VariationalSolver(I1, I2, I2x, _u, level - 1);
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if (flags & USE_MEDIAN_FILTERING) medianBlur(_u, _u, 3);
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if (flags & USE_MEDIAN_FILTERING) medianBlur(_u, _u, 3);
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I1_h.release();
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I2_h.release();
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I2x_h.release();
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u_h.release();
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U.release();
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U_h.release();
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I1_h.release();
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I2_h.release();
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I2x_h.release();
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u_h.release();
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U.release();
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U_h.release();
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}
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void StereoVar::FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
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{
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double scale = pow(pyrScale, (double) level);
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CvSize frmSize = cvSize((int) (u.cols * scale + 0.5), (int) (u.rows * scale + 0.5));
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Mat I1_h, I2_h, I2x_h, u_h;
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double scale = pow(pyrScale, (double) level);
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CvSize frmSize = cvSize((int) (u.cols * scale + 0.5), (int) (u.rows * scale + 0.5));
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Mat I1_h, I2_h, I2x_h, u_h;
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//scaling DOWN
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resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
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resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
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resize(u, u_h, frmSize, 0, 0, INTER_AREA);
|
||||
u_h.convertTo(u_h, u_h.type(), scale);
|
||||
I2x_h = diffX(I2_h);
|
||||
//scaling DOWN
|
||||
resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
|
||||
resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
|
||||
resize(u, u_h, frmSize, 0, 0, INTER_AREA);
|
||||
u_h.convertTo(u_h, u_h.type(), scale);
|
||||
I2x_h = diffX(I2_h);
|
||||
|
||||
switch (cycle) {
|
||||
case CYCLE_O:
|
||||
VariationalSolver(I1_h, I2_h, I2x_h, u_h, level);
|
||||
break;
|
||||
case CYCLE_V:
|
||||
VCycle_MyFAS(I1_h, I2_h, I2x_h, u_h, level);
|
||||
break;
|
||||
}
|
||||
switch (cycle) {
|
||||
case CYCLE_O:
|
||||
VariationalSolver(I1_h, I2_h, I2x_h, u_h, level);
|
||||
break;
|
||||
case CYCLE_V:
|
||||
VCycle_MyFAS(I1_h, I2_h, I2x_h, u_h, level);
|
||||
break;
|
||||
}
|
||||
|
||||
u_h.convertTo(u_h, u_h.type(), 1.0 / scale);
|
||||
u_h.convertTo(u_h, u_h.type(), 1.0 / scale);
|
||||
|
||||
//scaling UP
|
||||
resize(u_h, u, u.size(), 0, 0, INTER_CUBIC);
|
||||
//scaling UP
|
||||
resize(u_h, u, u.size(), 0, 0, INTER_CUBIC);
|
||||
|
||||
I1_h.release();
|
||||
I2_h.release();
|
||||
I2x_h.release();
|
||||
u_h.release();
|
||||
I1_h.release();
|
||||
I2_h.release();
|
||||
I2x_h.release();
|
||||
u_h.release();
|
||||
|
||||
level--;
|
||||
if ((flags & USE_AUTO_PARAMS) && (level < levels / 3)) {
|
||||
penalization = PENALIZATION_PERONA_MALIK;
|
||||
fi *= 100;
|
||||
flags -= USE_AUTO_PARAMS;
|
||||
autoParams();
|
||||
}
|
||||
if (flags & USE_MEDIAN_FILTERING) medianBlur(u, u, 3);
|
||||
if (level >= 0) FMG(I1, I2, I2x, u, level);
|
||||
level--;
|
||||
if ((flags & USE_AUTO_PARAMS) && (level < levels / 3)) {
|
||||
penalization = PENALIZATION_PERONA_MALIK;
|
||||
fi *= 100;
|
||||
flags -= USE_AUTO_PARAMS;
|
||||
autoParams();
|
||||
}
|
||||
if (flags & USE_MEDIAN_FILTERING) medianBlur(u, u, 3);
|
||||
if (level >= 0) FMG(I1, I2, I2x, u, level);
|
||||
}
|
||||
|
||||
void StereoVar::autoParams()
|
||||
{
|
||||
int maxD = MAX(labs(maxDisp), labs(minDisp));
|
||||
|
||||
if (!maxD) pyrScale = 0.85;
|
||||
else if (maxD < 8) pyrScale = 0.5;
|
||||
else if (maxD < 64) pyrScale = 0.5 + static_cast<double>(maxD - 8) * 0.00625;
|
||||
else pyrScale = 0.85;
|
||||
|
||||
if (maxD) {
|
||||
levels = 0;
|
||||
while ( pow(pyrScale, levels) * maxD > 1.5) levels ++;
|
||||
levels++;
|
||||
}
|
||||
{
|
||||
int maxD = MAX(labs(maxDisp), labs(minDisp));
|
||||
|
||||
switch(penalization) {
|
||||
case PENALIZATION_TICHONOV: cycle = CYCLE_V; break;
|
||||
case PENALIZATION_CHARBONNIER: cycle = CYCLE_O; break;
|
||||
case PENALIZATION_PERONA_MALIK: cycle = CYCLE_O; break;
|
||||
}
|
||||
if (!maxD) pyrScale = 0.85;
|
||||
else if (maxD < 8) pyrScale = 0.5;
|
||||
else if (maxD < 64) pyrScale = 0.5 + static_cast<double>(maxD - 8) * 0.00625;
|
||||
else pyrScale = 0.85;
|
||||
|
||||
if (maxD) {
|
||||
levels = 0;
|
||||
while ( pow(pyrScale, levels) * maxD > 1.5) levels ++;
|
||||
levels++;
|
||||
}
|
||||
|
||||
switch(penalization) {
|
||||
case PENALIZATION_TICHONOV: cycle = CYCLE_V; break;
|
||||
case PENALIZATION_CHARBONNIER: cycle = CYCLE_O; break;
|
||||
case PENALIZATION_PERONA_MALIK: cycle = CYCLE_O; break;
|
||||
}
|
||||
}
|
||||
|
||||
void StereoVar::operator ()( const Mat& left, const Mat& right, Mat& disp )
|
||||
{
|
||||
CV_Assert(left.size() == right.size() && left.type() == right.type());
|
||||
CvSize imgSize = left.size();
|
||||
int MaxD = MAX(labs(minDisp), labs(maxDisp));
|
||||
int SignD = 1; if (MIN(minDisp, maxDisp) < 0) SignD = -1;
|
||||
if (minDisp >= maxDisp) {MaxD = 256; SignD = 1;}
|
||||
|
||||
Mat u;
|
||||
if ((flags & USE_INITIAL_DISPARITY) && (!disp.empty())) {
|
||||
CV_Assert(disp.size() == left.size() && disp.type() == CV_8UC1);
|
||||
disp.convertTo(u, CV_32FC1, static_cast<double>(SignD * MaxD) / 256);
|
||||
} else {
|
||||
u.create(imgSize, CV_32FC1);
|
||||
u.setTo(0);
|
||||
}
|
||||
CV_Assert(left.size() == right.size() && left.type() == right.type());
|
||||
CvSize imgSize = left.size();
|
||||
int MaxD = MAX(labs(minDisp), labs(maxDisp));
|
||||
int SignD = 1; if (MIN(minDisp, maxDisp) < 0) SignD = -1;
|
||||
if (minDisp >= maxDisp) {MaxD = 256; SignD = 1;}
|
||||
|
||||
// Preprocessing
|
||||
Mat leftgray, rightgray;
|
||||
if (left.type() != CV_8UC1) {
|
||||
cvtColor(left, leftgray, CV_BGR2GRAY);
|
||||
cvtColor(right, rightgray, CV_BGR2GRAY);
|
||||
} else {
|
||||
left.copyTo(leftgray);
|
||||
right.copyTo(rightgray);
|
||||
}
|
||||
if (flags & USE_EQUALIZE_HIST) {
|
||||
equalizeHist(leftgray, leftgray);
|
||||
equalizeHist(rightgray, rightgray);
|
||||
}
|
||||
if (poly_sigma > 0.0001) {
|
||||
GaussianBlur(leftgray, leftgray, cvSize(poly_n, poly_n), poly_sigma);
|
||||
GaussianBlur(rightgray, rightgray, cvSize(poly_n, poly_n), poly_sigma);
|
||||
}
|
||||
|
||||
if (flags & USE_AUTO_PARAMS) {
|
||||
penalization = PENALIZATION_TICHONOV;
|
||||
autoParams();
|
||||
}
|
||||
Mat u;
|
||||
if ((flags & USE_INITIAL_DISPARITY) && (!disp.empty())) {
|
||||
CV_Assert(disp.size() == left.size() && disp.type() == CV_8UC1);
|
||||
disp.convertTo(u, CV_32FC1, static_cast<double>(SignD * MaxD) / 256);
|
||||
} else {
|
||||
u.create(imgSize, CV_32FC1);
|
||||
u.setTo(0);
|
||||
}
|
||||
|
||||
Mat I1, I2;
|
||||
leftgray.convertTo(I1, CV_32FC1);
|
||||
rightgray.convertTo(I2, CV_32FC1);
|
||||
leftgray.release();
|
||||
rightgray.release();
|
||||
// Preprocessing
|
||||
Mat leftgray, rightgray;
|
||||
if (left.type() != CV_8UC1) {
|
||||
cvtColor(left, leftgray, CV_BGR2GRAY);
|
||||
cvtColor(right, rightgray, CV_BGR2GRAY);
|
||||
} else {
|
||||
left.copyTo(leftgray);
|
||||
right.copyTo(rightgray);
|
||||
}
|
||||
if (flags & USE_EQUALIZE_HIST) {
|
||||
equalizeHist(leftgray, leftgray);
|
||||
equalizeHist(rightgray, rightgray);
|
||||
}
|
||||
if (poly_sigma > 0.0001) {
|
||||
GaussianBlur(leftgray, leftgray, cvSize(poly_n, poly_n), poly_sigma);
|
||||
GaussianBlur(rightgray, rightgray, cvSize(poly_n, poly_n), poly_sigma);
|
||||
}
|
||||
|
||||
Mat I2x = diffX(I2);
|
||||
|
||||
FMG(I1, I2, I2x, u, levels - 1);
|
||||
|
||||
I1.release();
|
||||
I2.release();
|
||||
I2x.release();
|
||||
|
||||
|
||||
disp.create( left.size(), CV_8UC1 );
|
||||
u = abs(u);
|
||||
u.convertTo(disp, disp.type(), 256 / MaxD, 0);
|
||||
if (flags & USE_AUTO_PARAMS) {
|
||||
penalization = PENALIZATION_TICHONOV;
|
||||
autoParams();
|
||||
}
|
||||
|
||||
u.release();
|
||||
Mat I1, I2;
|
||||
leftgray.convertTo(I1, CV_32FC1);
|
||||
rightgray.convertTo(I2, CV_32FC1);
|
||||
leftgray.release();
|
||||
rightgray.release();
|
||||
|
||||
Mat I2x = diffX(I2);
|
||||
|
||||
FMG(I1, I2, I2x, u, levels - 1);
|
||||
|
||||
I1.release();
|
||||
I2.release();
|
||||
I2x.release();
|
||||
|
||||
|
||||
disp.create( left.size(), CV_8UC1 );
|
||||
u = abs(u);
|
||||
u.convertTo(disp, disp.type(), 256 / MaxD, 0);
|
||||
|
||||
u.release();
|
||||
}
|
||||
} // namespace
|
||||
Reference in New Issue
Block a user