c++ - OpenCV float matrix summation returns -#1.IND -

i have matrix of type cv_32fc1 size 32x32, , values similar this:

1.93694e-008    3.07071e-008    4.94021e-008    7.62369e-008    1.18962e-007    1.76913e-007    2.59968e-007    3.67334e-007    4.95609e-007    6.40923e-007    7.78457e-007    8.7465e-007 9.11251e-007    8.31488e-007    6.44493e-007    3.5359e-007 1.04311e-012    -3.53588e-007   -6.44492e-007   -8.31487e-007   -9.1125e-007    -8.74649e-007   -7.78456e-007   -6.40922e-007   -4.95609e-007   -3.67334e-007   -2.59968e-007   -1.76913e-007   -1.18962e-007   -7.62369e-008   -4.94021e-008   -3.07071e-008    3.06892e-008    5.09824e-008    8.35426e-008    1.35964e-007    2.16775e-007    3.37835e-007    5.13594e-007    7.49976e-007    1.05257e-006    1.40219e-006    1.74842e-006    2.03448e-006    2.14198e-006    2.01039e-006    1.57129e-006    8.70235e-007    2.60888e-012    -8.62696e-007   -1.57507e-006   -2.00502e-006   -2.15194e-006   -2.02933e-006   -1.75414e-006   -1.40072e-006   -1.05049e-006   -7.50281e-007   -5.11113e-007   -3.37139e-007   -2.16334e-007   -1.35222e-007   -8.36318e-008   -5.08201e-008    4.92612e-008    8.35269e-008    1.43107e-007    2.39115e-007    3.9693e-007 6.44434e-007    1.01118e-006    1.54809e-006    2.24752e-006    3.09694e-006    4.02846e-006    4.76226e-006    5.19854e-006    4.91817e-006    3.91087e-006    2.13266e-006    5.87056e-012    -2.22993e-006   -3.90748e-006   -4.91911e-006   -5.15612e-006   -4.7527e-006    -3.97984e-006   -3.0987e-006    -2.24102e-006   -1.54625e-006   -1.02186e-006   -6.43699e-007   -4.02441e-007   -2.39679e-007   -1.44198e-007   -8.37019e-008    7.60845e-008    1.3579e-007 2.39106e-007    4.18485e-007    7.25225e-007    1.21709e-006    2.01066e-006    3.17691e-006    4.7935e-006 6.89156e-006    9.13404e-006    1.12809e-005    1.2473e-005 1.21505e-005    9.77994e-006    5.51596e-006    1.40501e-011    -5.44681e-006   -9.79417e-006   -1.21135e-005   -1.25166e-005   -1.12539e-005   -9.15874e-006   -6.88435e-006   -4.78444e-006   -3.17864e-006   -2.00114e-006   -1.21546e-006   -7.23496e-007   -4.16641e-007   -2.39246e-007   -1.35427e-007    1.17695e-007    2.16794e-007    3.94831e-007    7.2493e-007 1.28815e-006    2.29012e-006    3.89558e-006    6.44857e-006    1.01646e-005    1.50314e-005    2.0827e-005 2.63105e-005    2.98054e-005    2.97086e-005    2.40412e-005    1.36533e-005    3.31313e-011    -1.35655e-005   -2.41156e-005   -2.93022e-005   -2.9738e-005    -2.61076e-005   -2.06374e-005   -1.50235e-005   -1.01053e-005   -6.43866e-006   -3.91845e-006   -2.27538e-006   -1.30584e-006   -7.19624e-007   -3.99035e-007   -2.16132e-007    1.76896e-007    3.37326e-007    6.44178e-007    1.21603e-006    2.28783e-006    4.19597e-006    7.48731e-006    1.29483e-005    2.10391e-005    3.25671e-005    4.61848e-005    6.00322e-005    6.96929e-005    7.00884e-005    5.77746e-005    3.27704e-005    7.11531e-011    -3.32494e-005   -5.77843e-005   -7.02775e-005   -6.95844e-005   -6.01547e-005   -4.60997e-005   -3.26031e-005   -2.10729e-005   -1.29365e-005   -7.52144e-006   -4.19446e-006   -2.29502e-006   -1.21847e-006   -6.44452e-007   -3.37835e-007    2.57106e-007    5.12948e-007    1.00677e-006    2.00376e-006    3.89464e-006    7.47791e-006    1.39647e-005    2.49364e-005    4.25078e-005    6.76395e-005    9.88971e-005    0.000132626 0.000155259 0.000161028 0.000132103 7.82914e-005    1.46644e-010    -7.3509e-005    -0.000132428    -0.000157919    -0.000155513    -0.00013163 -9.86906e-005   -6.75702e-005   -4.23211e-005   -2.49209e-005   -1.39393e-005   -7.4401e-006    -3.907e-006 -1.98798e-006   -1.01118e-006   -5.10933e-007    3.66412e-007    7.50641e-007    1.54256e-006    3.17864e-006    6.4339e-006 1.29365e-005    2.49279e-005    4.6617e-005 8.16626e-005    0.00013382  0.000200838 0.000271401 0.000324457 0.00033432  0.000278377 0.000160663 2.93506e-010    -0.000159074    -0.000279156    -0.00033313 -0.000324805    -0.000271655    -0.000200502    -0.000134051    -8.16492e-005   -4.65018e-005   -2.50238e-005   -1.28558e-005   -6.4671e-006    -3.16087e-006   -1.54726e-006   -7.49108e-007    4.96402e-007    1.05131e-006    2.24852e-006    4.7824e-006 1.01559e-005    2.10192e-005    4.24649e-005    8.1663e-005 0.000147894 0.000248684 0.00037868  0.000520104 0.000625421 0.000644914 0.000542007 0.000308816 4.94443e-010    -0.000308816    -0.000542006    -0.000644913    -0.00062542 -0.000520103    -0.00037868 -0.000248684    -0.000147894    -8.1663e-005    -4.24649e-005   -2.10192e-005   -1.01559e-005   -4.7824e-006    -2.24852e-006   -1.05131e-006    6.37726e-007    1.40331e-006    3.08887e-006    6.87106e-006    1.50463e-005    3.2414e-005 6.76818e-005    0.000133569 0.000248639 0.000422184 0.00065146  0.000894996 0.00107579  0.00111096  0.000927537 0.000532558 7.58324e-010    -0.000530046    -0.000931273    -0.00110873 -0.0010804  -0.000894512    -0.000651227    -0.000422419    -0.000247185    -0.000133338    -6.72535e-005   -3.21678e-005   -1.50196e-005   -6.79725e-006   -3.09339e-006   -1.39594e-006    7.8135e-007 1.75357e-006    4.00828e-006    9.16832e-006    2.07321e-005    4.62177e-005    9.87761e-005    0.000200804 0.000378899 0.000651439 0.00101715  0.001382    0.00170613  0.00172519  0.0014902   0.000907568 1.27805e-009    -0.000711667    -0.00145754 -0.00165562 -0.00166379 -0.00137544 -0.00100386 -0.000651477    -0.000377943    -0.00020075 -9.89828e-005   -4.61232e-005   -2.08348e-005   -9.12724e-006   -4.02846e-006   -1.74893e-006    8.75488e-007    2.03129e-006    4.77681e-006    1.12062e-005    2.63779e-005    5.97129e-005    0.000132279 0.000271243 0.000518719 0.000895067 0.00138363  0.00187817  0.0023045   0.00226795  0.0020538   0.00102006  1.72359e-009    -0.00121603 -0.00207708 -0.00234277 -0.00233372 -0.00188639 -0.00138955 -0.000894997    -0.000516362    -0.000271206    -0.000131383    -5.95909e-005   -2.62789e-005   -1.11659e-005   -4.77324e-006   -2.02753e-006    9.03581e-007    2.15238e-006    5.13994e-006    1.25092e-005    2.9738e-005 6.96191e-005    0.000155494 0.000324651 0.000626541 0.00107783  0.00170289  0.00231382  0.00289925  0.00319172  0.00261321  0.00238429  1.36055e-009    -0.000849137    -0.0024097  -0.00265846 -0.00264856 -0.00225427 -0.00162514 -0.00107645 -0.000618912    -0.000324755    -0.000155024    -6.93965e-005   -2.98054e-005   -1.23755e-005   -5.17234e-006   -2.13743e-006    8.27761e-007    2.00502e-006    4.91775e-006    1.20539e-005    2.95986e-005    6.97392e-005    0.000158433 0.00033465  0.000639953 0.00111074  0.00175592  0.00230024  0.00322278  0.00300945  0.00326031  0.00219442  4.62512e-009    -0.000912749    -0.00310091 -0.0025526  -0.00304301 -0.00225057 -0.00171355 -0.00111096 -0.000643998    -0.000334534    -0.000160302    -6.98654e-005   -2.97312e-005   -1.20909e-005   -4.91752e-006   -2.00764e-006    6.38724e-007    1.57426e-006    3.89932e-006    9.75503e-006    2.41757e-005    5.78145e-005    0.000132428 0.000279769 0.000540863 0.000931931 0.00145754  0.00207555  0.00251042  0.00324973  0.00201045  0.00161779  7.41874e-011    -0.000522181    -0.00181798 -0.00263501 -0.00225157 -0.00201341 -0.0013802  -0.000930472    -0.000533438    -0.000280075    -0.000131644    -5.78408e-005   -2.40784e-005   -9.69801e-006   -3.90271e-006   -1.56684e-006    3.44954e-007    8.62074e-007    2.17136e-006    5.37491e-006    1.35922e-005    3.23668e-005    7.29956e-005    0.00016042  0.000302819 0.000531468 0.000975368 0.00121603  0.00232883  0.00300655  0.00149493  0.000624032 7.95393e-012    -5.55596e-007   -0.000888571    -0.000432224    -0.00123506 -0.000952354    -0.000728262    -0.000531968    -0.000312754    -0.000160104    -7.88826e-005   -3.3019e-005    -1.36507e-005   -5.51597e-006   -2.12216e-006   -8.69612e-007    5.44375e-013    1.17471e-012    2.91405e-012    6.54259e-012    1.4955e-011 3.40302e-011    6.7263e-011 1.31421e-010    2.25234e-010    3.41047e-010    4.01706e-010    7.48939e-010    2.73395e-010    1.42528e-009    1.58768e-011    2.8661e-012 0   -1.#ind -1.#ind -1.#ind 0   0   0   0   0   0   0   0   0   0   0   0    -3.44955e-007   -8.69609e-007   -2.12216e-006   -5.51595e-006   -1.36507e-005   -3.30189e-005   -7.88824e-005   -0.000160104    -0.000312753    -0.000531968    -0.000728261    -0.000952353    -0.00123506 -0.000432223    -0.00088857 -5.55596e-007   -1.78564e-012   0.000624032 0.00149493  0.00300655  0.00232883  0.00121603  0.000975369 0.000531468 0.000302819 0.000160421 7.29957e-005    3.23669e-005    1.35922e-005    5.37492e-006    2.17136e-006    8.62078e-007     -6.38724e-007   -1.56684e-006   -3.90271e-006   -9.698e-006 -2.40784e-005   -5.78408e-005   -0.000131644    -0.000280074    -0.000533438    -0.000930472    -0.0013802  -0.00201341 -0.00225157 -0.00263501 -0.00181798 -0.000522181    -1.66549e-011   0.00161779  0.00201045  0.00324973  0.00251042  0.00207555  0.00145754  0.000931931 0.000540864 0.00027977  0.000132428 5.78145e-005    2.41758e-005    9.75504e-006    3.89932e-006    1.57426e-006     -8.27762e-007   -2.00764e-006   -4.91751e-006   -1.20909e-005   -2.97312e-005   -6.98654e-005   -0.000160302    -0.000334534    -0.000643998    -0.00111096 -0.00171354 -0.00225057 -0.00304301 -0.0025526  -0.00310091 -0.000912749    -1.03833e-009   0.00219442  0.00326031  0.00300945  0.00322278  0.00230024  0.00175592  0.00111074  0.000639954 0.00033465  0.000158433 6.97392e-005    2.95986e-005    1.20539e-005    4.91775e-006    2.00503e-006     -9.03582e-007   -2.13743e-006   -5.17234e-006   -1.23755e-005   -2.98054e-005   -6.93965e-005   -0.000155024    -0.000324755    -0.000618912    -0.00107645 -0.00162514 -0.00225427 -0.00264856 -0.00265846 -0.0024097  -0.000849137    -3.05441e-010   0.00238428  0.00261321  0.00319172  0.00289925  0.00231382  0.00170289  0.00107783  0.000626541 0.000324651 0.000155494 6.96191e-005    2.9738e-005 1.25092e-005    5.13994e-006    2.15238e-006     -8.75488e-007   -2.02753e-006   -4.77324e-006   -1.11659e-005   -2.62789e-005   -5.95909e-005   -0.000131383    -0.000271206    -0.000516362    -0.000894997    -0.00138955 -0.00188639 -0.00233372 -0.00234277 -0.00207708 -0.00121603 -3.86942e-010   0.00102006  0.00205379  0.00226795  0.0023045   0.00187817  0.00138363  0.000895067 0.000518719 0.000271243 0.000132279 5.97129e-005    2.63779e-005    1.12062e-005    4.77681e-006    2.03129e-006     -7.8135e-007    -1.74893e-006   -4.02846e-006   -9.12724e-006   -2.08348e-005   -4.61232e-005   -9.89828e-005   -0.00020075 -0.000377943    -0.000651477    -0.00100386 -0.00137544 -0.00166379 -0.00165562 -0.00145754 -0.000711667    -2.86921e-010   0.000907568 0.0014902   0.00172519  0.00170613  0.001382    0.00101715  0.000651439 0.000378899 0.000200805 9.87761e-005    4.62178e-005    2.07321e-005    9.16832e-006    4.00828e-006    1.75357e-006     -6.37726e-007   -1.39594e-006   -3.09339e-006   -6.79725e-006   -1.50196e-005   -3.21678e-005   -6.72535e-005   -0.000133338    -0.000247185    -0.000422419    -0.000651227    -0.000894512    -0.0010804  -0.00110873 -0.000931273    -0.000530046    -1.70242e-010   0.000532558 0.000927537 0.00111096  0.00107579  0.000894996 0.00065146  0.000422184 0.000248639 0.000133569 6.76818e-005    3.2414e-005 1.50463e-005    6.87106e-006    3.08887e-006    1.40331e-006     -4.96402e-007   -1.05131e-006   -2.24852e-006   -4.7824e-006    -1.01559e-005   -2.10192e-005   -4.24649e-005   -8.1663e-005    -0.000147894    -0.000248684    -0.00037868 -0.000520104    -0.00062542 -0.000644914    -0.000542007    -0.000308816    -1.11001e-010   0.000308816 0.000542006 0.000644914 0.00062542  0.000520104 0.00037868  0.000248684 0.000147894 8.1663e-005 4.24649e-005    2.10192e-005    1.01559e-005    4.7824e-006 2.24852e-006    1.05131e-006     -3.66412e-007   -7.49107e-007   -1.54726e-006   -3.16087e-006   -6.4671e-006    -1.28558e-005   -2.50238e-005   -4.65018e-005   -8.16492e-005   -0.000134051    -0.000200502    -0.000271655    -0.000324805    -0.00033313 -0.000279156    -0.000159074    -6.58915e-011   0.000160663 0.000278377 0.00033432  0.000324457 0.000271401 0.000200838 0.00013382  8.16626e-005    4.6617e-005 2.49279e-005    1.29365e-005    6.4339e-006 3.17864e-006    1.54256e-006    7.50641e-007     -2.57106e-007   -5.10933e-007   -1.01118e-006   -1.98798e-006   -3.907e-006 -7.4401e-006    -1.39393e-005   -2.49209e-005   -4.23211e-005   -6.75702e-005   -9.86906e-005   -0.00013163 -0.000155513    -0.00015792 -0.000132428    -7.35091e-005   -3.29212e-011   7.82913e-005    0.000132103 0.000161028 0.000155259 0.000132626 9.88971e-005    6.76395e-005    4.25078e-005    2.49364e-005    1.39647e-005    7.47791e-006    3.89464e-006    2.00376e-006    1.00677e-006    5.12948e-007     -1.76896e-007   -3.37835e-007   -6.44452e-007   -1.21847e-006   -2.29502e-006   -4.19446e-006   -7.52144e-006   -1.29365e-005   -2.10729e-005   -3.26031e-005   -4.60997e-005   -6.01547e-005   -6.95844e-005   -7.02776e-005   -5.77843e-005   -3.32494e-005   -1.59737e-011   3.27703e-005    5.77745e-005    7.00883e-005    6.96929e-005    6.00322e-005    4.61848e-005    3.25671e-005    2.10391e-005    1.29483e-005    7.48731e-006    4.19597e-006    2.28783e-006    1.21603e-006    6.44178e-007    3.37326e-007     -1.17695e-007   -2.16132e-007   -3.99035e-007   -7.19624e-007   -1.30584e-006   -2.27538e-006   -3.91845e-006   -6.43866e-006   -1.01053e-005   -1.50235e-005   -2.06374e-005   -2.61076e-005   -2.9738e-005    -2.93022e-005   -2.41156e-005   -1.35655e-005   -7.43791e-012   1.36532e-005    2.40412e-005    2.97086e-005    2.98054e-005    2.63105e-005    2.0827e-005 1.50314e-005    1.01646e-005    6.44857e-006    3.89558e-006    2.29012e-006    1.28815e-006    7.2493e-007 3.94831e-007    2.16794e-007     -7.60845e-008   -1.35427e-007   -2.39246e-007   -4.16641e-007   -7.23496e-007   -1.21546e-006   -2.00114e-006   -3.17864e-006   -4.78444e-006   -6.88435e-006   -9.15875e-006   -1.12539e-005   -1.25166e-005   -1.21135e-005   -9.79418e-006   -5.44681e-006   -3.15423e-012   5.51595e-006    9.77993e-006    1.21505e-005    1.2473e-005 1.12809e-005    9.13404e-006    6.89155e-006    4.79349e-006    3.17691e-006    2.01066e-006    1.21709e-006    7.25225e-007    4.18485e-007    2.39106e-007    1.3579e-007  -4.92612e-008   -8.37019e-008   -1.44198e-007   -2.39679e-007   -4.02441e-007   -6.43699e-007   -1.02186e-006   -1.54625e-006   -2.24102e-006   -3.0987e-006    -3.97984e-006   -4.7527e-006    -5.15612e-006   -4.91911e-006   -3.90748e-006   -2.22994e-006   -1.31793e-012   2.13266e-006    3.91087e-006    4.91817e-006    5.19854e-006    4.76226e-006    4.02846e-006    3.09694e-006    2.24752e-006    1.54809e-006    1.01118e-006    6.44434e-007    3.9693e-007 2.39115e-007    1.43107e-007    8.35269e-008     -3.06892e-008   -5.08201e-008   -8.36318e-008   -1.35222e-007   -2.16334e-007   -3.37139e-007   -5.11114e-007   -7.50282e-007   -1.05049e-006   -1.40072e-006   -1.75414e-006   -2.02933e-006   -2.15195e-006   -2.00503e-006   -1.57507e-006   -8.62697e-007   -5.85689e-013   8.70233e-007    1.57129e-006    2.01038e-006    2.14198e-006    2.03448e-006    1.74842e-006    1.40219e-006    1.05257e-006    7.49976e-007    5.13594e-007    3.37835e-007    2.16775e-007    1.35964e-007    8.35426e-008    5.09824e-008 

after getting summation:

float sum = cv::sum(inputmat)[0]; 

the result -1.#ind, know means indefinite. double-check, tried getting summation pixel pixel in loop instead again returns -1.#ind. in matlab, same matrix summation gives me 0.0254. there way same result in opencv? thank you.

edit

here code getting inputmat:

cv::mat image = cv::imread("test.png", cv_load_image_grayscale); cv::mat blkimg = image.rowrange(0, 24).colrange(0, 24); cv::mat blk; blkimg.copyto(blk);  // kernel mat outside cv::multiply(blk, kernel, blk); cv::mat padded, blkfft; cv::copymakeborder(blk, padded, 0, 8, 0, 8, cv::border_constant, cv::scalar::all(0)); cv::mat planes[] = { cv::mat_<float>(padded), cv::mat::zeros(padded.size(), cv_32fc1) }; cv::mat complexblk; cv::merge(planes, 2, complexblk); cv::dft(complexblk, blkfft); cv::split(blkfft, dftchannels);  cv::mat mul1, mul2; cv::multiply(dftchannels[0], dbpass, mul1); // dbpass comes outside, of size 32x32 cv::multiply(dftchannels[1], dbpass, mul2); // dbpass comes outside, of size 32x32 cv::mat blkfftabs = getabs(mul1, mul2); cv::mat inputmat; cv::multiply(blkfftabs, blkfftabs, inputmat); cv::multiply(inputmat, sth, inputmat); // sth mat comes outside, of size 32x32, type cv_32fc1; 

function getabs defined follows:

cv::mat getabs(cv::mat ch1, cv::mat  ch2) {     int rows = ch1.rows;     int cols = ch1.cols;      cv::mat absmat = cv::mat(rows, cols, ch1.type());     int count = 0;      (int = 0; < rows; i++)     {         (int j = 0; j < cols; j++)         {             float realval = ch1.at<float>(i, j);             float imval = ch2.at<float>(i, j);             float absval = std::sqrt(realval*realval + imval*imval);             absmat.at<float>(i, j) = absval;         }     }      return absmat; }