diff --git a/modules/core/include/opencv2/core.hpp b/modules/core/include/opencv2/core.hpp
index be800333f8..f6372ac03e 100644
--- a/modules/core/include/opencv2/core.hpp
+++ b/modules/core/include/opencv2/core.hpp
@@ -912,11 +912,8 @@ CV_EXPORTS_W void reduceArgMax(InputArray src, OutputArray dst, int axis, bool l
 
 The function cv::minMaxIdx finds the minimum and maximum element values and their positions. The
 extremums are searched across the whole array or, if mask is not an empty array, in the specified
-array region. The function does not work with multi-channel arrays. If you need to find minimum or
-maximum elements across all the channels, use Mat::reshape first to reinterpret the array as
-single-channel. Or you may extract the particular channel using either extractImageCOI, or
-mixChannels, or split. In case of a sparse matrix, the minimum is found among non-zero elements
-only.
+array region. In case of a sparse matrix, the minimum is found among non-zero elements
+only. Multi-channel input is supported without mask and extremums indexes (should be nullptr).
 @note When minIdx is not NULL, it must have at least 2 elements (as well as maxIdx), even if src is
 a single-row or single-column matrix. In OpenCV (following MATLAB) each array has at least 2
 dimensions, i.e. single-column matrix is Mx1 matrix (and therefore minIdx/maxIdx will be
diff --git a/modules/core/src/minmax.cpp b/modules/core/src/minmax.cpp
index ff3786886e..b5aa4c8462 100644
--- a/modules/core/src/minmax.cpp
+++ b/modules/core/src/minmax.cpp
@@ -1510,9 +1510,19 @@ void cv::minMaxIdx(InputArray _src, double* minVal,
 
     Mat src = _src.getMat(), mask = _mask.getMat();
 
+    int _minIdx, _maxIdx;
+    int* min_offset = (cn == 1) ? minIdx : &_minIdx;
+    int* max_offset = (cn == 1) ? maxIdx : &_maxIdx;
     if (src.dims <= 2)
-        CALL_HAL(minMaxIdx, cv_hal_minMaxIdx, src.data, src.step, src.cols, src.rows, src.depth(), minVal, maxVal,
-                 minIdx, maxIdx, mask.data);
+    {
+        CALL_HAL(minMaxIdx, cv_hal_minMaxIdx, src.data, src.step, src.cols*cn, src.rows, src.depth(),
+                    minVal, maxVal, min_offset, max_offset, mask.data);
+    }
+    else if (src.isContinuous())
+    {
+        CALL_HAL(minMaxIdx, cv_hal_minMaxIdx, src.data, 0, (int)src.total()*cn, 1, src.depth(),
+                 minVal, maxVal, min_offset, max_offset, mask.data);
+    }
 
     CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_MINMAXLOC>(src.cols, src.rows),
                openvx_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))