opencv中为一个Mat类赋值并改变它的值、remap_opencv c++如何将mat中大于某个值的元素改为固定值-优快云博客

本文链接：https://blog.youkuaiyun.com/weixin_41484240/article/details/80638448

本文介绍了如何在OpenCV中为Mat类赋值并改变其值，重点讲解了remap函数的使用，包括convertMaps的转换操作和remap的图像几何变换。convertMaps可以将浮点数映射转换为更紧凑、更快的固定点表示，而remap则利用这些映射对图像进行重映射，实现像素的非整数坐标计算。

Mat
const int BLOCK_SZ = 64;
short XY[BLOCK_SZ*BLOCK_SZ * 2], A[BLOCK_SZ*BLOCK_SZ];

其中XY和A是一个已知大小的容器：

Mat _XY(bh, bw, CV_16SC2, XY), matA;

short* xy = XY + y1*bw * 2;

short* alpha = A + y1*bw;

Mat _matA(bh, bw, CV_16U, A);

这样，改变XY的值就能改变_XY的值，_MatA和A也是，alpha和A（这个是指针）。

Remap

convertMaps

Converts image transformation maps from one representation to another.

C++: void convertMaps (InputArray map1, InputArray map2, OutputArray dstmap1, OutputArray dstmap2, int dstmap1type, bool nninterpolation=false )

Python: cv2. convertMaps (map1, map2, dstmap1type [, dstmap1 [, dstmap2 [, nninterpolation ] ] ] ) → dstmap1, dstmap2

Parameters:

Parameters:	map1 – The first input map of type `CV_16SC2` , `CV_32FC1` , or `CV_32FC2` . map2 – The second input map of type `CV_16UC1` , `CV_32FC1` , or none (empty matrix), respectively. dstmap1 – The first output map that has the type `dstmap1type` and the same size as `src` . dstmap2 – The second output map. dstmap1type – Type of the first output map that should be `CV_16SC2` , `CV_32FC1` , or `CV_32FC2` . nninterpolation – Flag indicating whether the fixed-point maps are used for the nearest-neighbor or for a more complex interpolation.

map1 – The first input map of type CV_16SC2 , CV_32FC1 , or CV_32FC2 .
map2 – The second input map of type CV_16UC1 , CV_32FC1 , or none (empty matrix), respectively.
dstmap1 – The first output map that has the type dstmap1type and the same size as src .
dstmap2 – The second output map.
dstmap1type – Type of the first output map that should be CV_16SC2 , CV_32FC1 , or CV_32FC2 .
nninterpolation – Flag indicating whether the fixed-point maps are used for the nearest-neighbor or for a more complex interpolation.

The function converts a pair of maps for remap() from one representation to another. The following options ( (map1.type(), map2.type()) $\rightarrow$ (dstmap1.type(), dstmap2.type()) ) are supported:

$\texttt{(CV\_32FC1, CV\_32FC1)} \rightarrow \texttt{(CV\_16SC2, CV\_16UC1)}$ . This is the most frequently used conversion operation, in which the original floating-point maps (see remap() ) are converted to a more compact and much faster fixed-point representation. The first output array contains the rounded coordinates and the second array (created only when nninterpolation=false ) contains indices in the interpolation tables.
$\texttt{(CV\_32FC2)} \rightarrow \texttt{(CV\_16SC2, CV\_16UC1)}$ . The same as above but the original maps are stored in one 2-channel matrix.
Reverse conversion. Obviously, the reconstructed floating-point maps will not be exactly the same as the originals.

remap

Applies a generic geometrical transformation to an image.

C++: void remap (InputArray src, OutputArray dst, InputArray map1, InputArray map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar() )

Python: cv2. remap (src, map1, map2, interpolation [, dst [, borderMode [, borderValue ] ] ] ) → dst

C: void cvRemap (const CvArr* src, CvArr* dst, const CvArr* mapx, const CvArr* mapy, int flags=CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, CvScalar fillval=cvScalarAll(0) )

Python: cv. Remap (src, dst, mapx, mapy, flags=CV_INNER_LINEAR+CV_WARP_FILL_OUTLIERS, fillval=(0, 0, 0, 0) ) → None

Parameters:

Parameters:	src – Source image. dst – Destination image. It has the same size as `map1` and the same type as `src` . map1 – The first map of either `(x,y)` points or just `x` values having the type `CV_16SC2` , `CV_32FC1` , or `CV_32FC2` . See `convertMaps()` for details on converting a floating point representation to fixed-point for speed. map2 – The second map of `y` values having the type `CV_16UC1` , `CV_32FC1` , or none (empty map if `map1` is `(x,y)` points), respectively. interpolation – Interpolation method (see `resize()` ). The method `INTER_AREA` is not supported by this function. borderMode – Pixel extrapolation method (see `borderInterpolate()` ). When `borderMode=BORDER_TRANSPARENT` , it means that the pixels in the destination image that corresponds to the “outliers” in the source image are not modified by the function. borderValue – Value used in case of a constant border. By default, it is 0.

src – Source image.
dst – Destination image. It has the same size as map1 and the same type as src .
map1 – The first map of either (x,y) points or just x values having the type CV_16SC2 , CV_32FC1 , or CV_32FC2 . See convertMaps() for details on converting a floating point representation to fixed-point for speed.
map2 – The second map of y values having the type CV_16UC1 , CV_32FC1 , or none (empty map if map1 is (x,y) points), respectively.
interpolation – Interpolation method (see resize() ). The method INTER_AREA is not supported by this function.
borderMode – Pixel extrapolation method (see borderInterpolate() ). When borderMode=BORDER_TRANSPARENT , it means that the pixels in the destination image that corresponds to the “outliers” in the source image are not modified by the function.
borderValue – Value used in case of a constant border. By default, it is 0.

The function remap transforms the source image using the specified map:

$\texttt{dst} (x,y) = \texttt{src} (map_x(x,y),map_y(x,y))$

where values of pixels with non-integer coordinates are computed using one of available interpolation methods. $map_x$ and $map_y$ can be encoded as separate floating-point maps in $map_1$ and $map_2$ respectively, or interleaved floating-point maps of $(x,y)$ in $map_1$ , or fixed-point maps created by using convertMaps() . The reason you might want to convert from floating to fixed-point representations of a map is that they can yield much faster (~2x) remapping operations. In the converted case, $map_1$ contains pairs (cvFloor(x), cvFloor(y)) and $map_2$ contains indices in a table of interpolation coefficients.