diff --git a/modules/gpu/src/arithm.cpp b/modules/gpu/src/arithm.cpp
index 8e9a2151f2..ba64111a96 100644
--- a/modules/gpu/src/arithm.cpp
+++ b/modules/gpu/src/arithm.cpp
@@ -492,10 +492,10 @@ namespace cv { namespace gpu { namespace mathfunc
     void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
 
     template <typename T>
-    void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum);
+    void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
 
     template <typename T>
-    void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum);
+    void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
 
     namespace sum
     {
@@ -543,9 +543,8 @@ Scalar cv::gpu::sqrSum(const GpuMat& src)
 Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf) 
 {
     using namespace mathfunc;
-    CV_Assert(src.channels() == 1);
 
-    typedef void (*Caller)(const DevMem2D, PtrStep, double*);
+    typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
     static const Caller callers[2][7] = 
         { { sqsum_multipass_caller<unsigned char>, sqsum_multipass_caller<char>, 
             sqsum_multipass_caller<unsigned short>, sqsum_multipass_caller<short>, 
@@ -555,15 +554,15 @@ Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
             sqsum_caller<int>, sqsum_caller<float>, 0 } };
 
     Size bufSize;
-    sum::get_buf_size_required(src.cols, src.rows, 1, bufSize.width, bufSize.height); 
+    sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height); 
     buf.create(bufSize, CV_8U);
 
-    Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
+    Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
     if (!caller) CV_Error(CV_StsBadArg, "sqrSum: unsupported type");
 
-    double result;
-    caller(src, buf, &result);
-    return result;
+    double result[4];
+    caller(src, buf, result, src.channels());
+    return Scalar(result[0], result[1], result[2], result[3]);
 }
 
 ////////////////////////////////////////////////////////////////////////
diff --git a/modules/gpu/src/cuda/mathfunc.cu b/modules/gpu/src/cuda/mathfunc.cu
index f7bc2cb3af..08e749f8b6 100644
--- a/modules/gpu/src/cuda/mathfunc.cu
+++ b/modules/gpu/src/cuda/mathfunc.cu
@@ -1989,7 +1989,7 @@ namespace cv { namespace gpu { namespace mathfunc
 
 
     template <typename T>
-    void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum)
+    void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn)
     {
         using namespace sum;
         typedef typename SumType<T>::R R;
@@ -1998,27 +1998,54 @@ namespace cv { namespace gpu { namespace mathfunc
         estimate_thread_cfg(src.cols, src.rows, threads, grid);
         set_kernel_consts(src.cols, src.rows, threads, grid);
 
-        sum_kernel<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
-                src, (typename TypeVec<R, 1>::vec_t*)buf.ptr(0));
-        sum_pass2_kernel<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
-                (typename TypeVec<R, 1>::vec_t*)buf.ptr(0), grid.x * grid.y);
+        switch (cn)
+        {
+        case 1:
+            sum_kernel<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 1>::vec_t*)buf.ptr(0));
+            sum_pass2_kernel<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
+                    (typename TypeVec<R, 1>::vec_t*)buf.ptr(0), grid.x * grid.y);
+            break;
+        case 2:
+            sum_kernel_C2<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 2>::vec_t*)buf.ptr(0));
+            sum_pass2_kernel_C2<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
+                    (typename TypeVec<R, 2>::vec_t*)buf.ptr(0), grid.x * grid.y);
+            break;
+        case 3:
+            sum_kernel_C3<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 3>::vec_t*)buf.ptr(0));
+            sum_pass2_kernel_C3<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
+                    (typename TypeVec<R, 3>::vec_t*)buf.ptr(0), grid.x * grid.y);
+            break;
+        case 4:
+            sum_kernel_C4<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 4>::vec_t*)buf.ptr(0));
+            sum_pass2_kernel_C4<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
+                    (typename TypeVec<R, 4>::vec_t*)buf.ptr(0), grid.x * grid.y);
+            break;
+        }
         cudaSafeCall(cudaThreadSynchronize());
 
-        R result = 0;
-        cudaSafeCall(cudaMemcpy(&result, buf.ptr(0), sizeof(R), cudaMemcpyDeviceToHost));
-        sum[0] = result;
+        R result[4] = {0, 0, 0, 0};
+        cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
+
+        sum[0] = result[0];
+        sum[1] = result[1];
+        sum[2] = result[2];
+        sum[3] = result[3];
     }  
 
-    template void sqsum_multipass_caller<unsigned char>(const DevMem2D, PtrStep, double*);
-    template void sqsum_multipass_caller<char>(const DevMem2D, PtrStep, double*);
-    template void sqsum_multipass_caller<unsigned short>(const DevMem2D, PtrStep, double*);
-    template void sqsum_multipass_caller<short>(const DevMem2D, PtrStep, double*);
-    template void sqsum_multipass_caller<int>(const DevMem2D, PtrStep, double*);
-    template void sqsum_multipass_caller<float>(const DevMem2D, PtrStep, double*);
+    template void sqsum_multipass_caller<unsigned char>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_multipass_caller<char>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_multipass_caller<unsigned short>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_multipass_caller<short>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_multipass_caller<int>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_multipass_caller<float>(const DevMem2D, PtrStep, double*, int);
 
 
     template <typename T>
-    void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum)
+    void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn)
     {
         using namespace sum;
         typedef typename SumType<T>::R R;
@@ -2027,20 +2054,42 @@ namespace cv { namespace gpu { namespace mathfunc
         estimate_thread_cfg(src.cols, src.rows, threads, grid);
         set_kernel_consts(src.cols, src.rows, threads, grid);
 
-        sum_kernel<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
-                src, (typename TypeVec<R, 1>::vec_t*)buf.ptr(0));
+        switch (cn)
+        {
+        case 1:
+            sum_kernel<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 1>::vec_t*)buf.ptr(0));
+            break;
+        case 2:
+            sum_kernel_C2<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 2>::vec_t*)buf.ptr(0));
+            break;
+        case 3:
+            sum_kernel_C3<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 3>::vec_t*)buf.ptr(0));
+            break;
+        case 4:
+            sum_kernel_C4<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>(
+                    src, (typename TypeVec<R, 4>::vec_t*)buf.ptr(0));
+            break;
+        }
         cudaSafeCall(cudaThreadSynchronize());
 
-        R result = 0;
-        cudaSafeCall(cudaMemcpy(&result, buf.ptr(0), sizeof(R), cudaMemcpyDeviceToHost));
-        sum[0] = result;
-    }  
+        R result[4] = {0, 0, 0, 0};
+        cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
 
-    template void sqsum_caller<unsigned char>(const DevMem2D, PtrStep, double*);
-    template void sqsum_caller<char>(const DevMem2D, PtrStep, double*);
-    template void sqsum_caller<unsigned short>(const DevMem2D, PtrStep, double*);
-    template void sqsum_caller<short>(const DevMem2D, PtrStep, double*);
-    template void sqsum_caller<int>(const DevMem2D, PtrStep, double*);
-    template void sqsum_caller<float>(const DevMem2D, PtrStep, double*);
+        sum[0] = result[0];
+        sum[1] = result[1];
+        sum[2] = result[2];
+        sum[3] = result[3];
+    }
+
+    template void sqsum_caller<unsigned char>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_caller<char>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_caller<unsigned short>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_caller<short>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_caller<int>(const DevMem2D, PtrStep, double*, int);
+    template void sqsum_caller<float>(const DevMem2D, PtrStep, double*, int);
 }}}
 
+
diff --git a/tests/gpu/src/arithm.cpp b/tests/gpu/src/arithm.cpp
index 69a8f47198..7dc7ba3a4e 100644
--- a/tests/gpu/src/arithm.cpp
+++ b/tests/gpu/src/arithm.cpp
@@ -983,6 +983,7 @@ struct CV_GpuSumTest: CvTest
                 }
                 if (type != CV_8S)
                 {
+                    gen(1 + rand() % 200, 1 + rand() % 200, CV_MAKETYPE(type, 1), src);
                     b = sqrSum(GpuMat(src));
                     Mat sqrsrc;
                     multiply(src, src, sqrsrc);
@@ -993,6 +994,36 @@ struct CV_GpuSumTest: CvTest
                         ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
                         return;
                     }
+                    gen(1 + rand() % 200, 1 + rand() % 200, CV_MAKETYPE(type, 2), src);
+                    b = sqrSum(GpuMat(src));
+                    multiply(src, src, sqrsrc);
+                    a = sum(sqrsrc);
+                    if (abs(a[0] - b[0]) + abs(a[1] - b[1])> src.size().area() * max_err * 2)
+                    {
+                        ts->printf(CvTS::CONSOLE, "type: %d, cols: %d, rows: %d, expected: %f, actual: %f\n", type, src.cols, src.rows, a[0], b[0]);
+                        ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                        return;
+                    }
+                    gen(1 + rand() % 200, 1 + rand() % 200, CV_MAKETYPE(type, 3), src);
+                    b = sqrSum(GpuMat(src));
+                    multiply(src, src, sqrsrc);
+                    a = sum(sqrsrc);
+                    if (abs(a[0] - b[0]) + abs(a[1] - b[1]) + abs(a[2] - b[2])> src.size().area() * max_err * 3)
+                    {
+                        ts->printf(CvTS::CONSOLE, "type: %d, cols: %d, rows: %d, expected: %f, actual: %f\n", type, src.cols, src.rows, a[0], b[0]);
+                        ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                        return;
+                    }
+                    gen(1 + rand() % 200, 1 + rand() % 200, CV_MAKETYPE(type, 4), src);
+                    b = sqrSum(GpuMat(src));
+                    multiply(src, src, sqrsrc);
+                    a = sum(sqrsrc);
+                    if (abs(a[0] - b[0]) + abs(a[1] - b[1]) + abs(a[2] - b[2]) + abs(a[3] - b[3])> src.size().area() * max_err * 4)
+                    {
+                        ts->printf(CvTS::CONSOLE, "type: %d, cols: %d, rows: %d, expected: %f, actual: %f\n", type, src.cols, src.rows, a[0], b[0]);
+                        ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                        return;
+                    }
                 }
             }
         }