Photo_clone

列挙型
enum	{ cv::NORMAL_CLONE = 1 , cv::MIXED_CLONE = 2 , cv::MONOCHROME_TRANSFER = 3 }
	seamlessClone algorithm flags [詳解]

関数
CV_EXPORTS_W void	cv::seamlessClone (InputArray src, InputArray dst, InputArray mask, Point p, OutputArray blend, int flags)
	Image editing tasks concern either global changes (color/intensity corrections, filters, deformations) or local changes concerned to a selection. Here we are interested in achieving local changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless manner. The extent of the changes ranges from slight distortions to complete replacement by novel content [PM03] . [詳解]
CV_EXPORTS_W void	cv::colorChange (InputArray src, InputArray mask, OutputArray dst, float red_mul=1.0f, float green_mul=1.0f, float blue_mul=1.0f)
	Given an original color image, two differently colored versions of this image can be mixed seamlessly. [詳解]
CV_EXPORTS_W void	cv::illuminationChange (InputArray src, InputArray mask, OutputArray dst, float alpha=0.2f, float beta=0.4f)
	Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image. [詳解]
CV_EXPORTS_W void	cv::textureFlattening (InputArray src, InputArray mask, OutputArray dst, float low_threshold=30, float high_threshold=45, int kernel_size=3)
	By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect. Here Canny Edge Detector is used. [詳解]

詳解

列挙型詳解

anonymous enum

anonymous enum

seamlessClone algorithm flags

列挙値
NORMAL_CLONE	The power of the method is fully expressed when inserting objects with complex outlines into a new background
MIXED_CLONE	The classic method, color-based selection and alpha masking might be time consuming and often leaves an undesirable halo. Seamless cloning, even averaged with the original image, is not effective. Mixed seamless cloning based on a loose selection proves effective.
MONOCHROME_TRANSFER	Monochrome transfer allows the user to easily replace certain features of one object by alternative features.

関数詳解

colorChange()

CV_EXPORTS_W void cv::colorChange	(	InputArray	src,
		InputArray	mask,
		OutputArray	dst,
		float	red_mul = 1.0f,
		float	green_mul = 1.0f,
		float	blue_mul = 1.0f
	)

Given an original color image, two differently colored versions of this image can be mixed seamlessly.

引数

src	Input 8-bit 3-channel image.
mask	Input 8-bit 1 or 3-channel image.
dst	Output image with the same size and type as src .
red_mul	R-channel multiply factor.
green_mul	G-channel multiply factor.
blue_mul	B-channel multiply factor.

Multiplication factor is between .5 to 2.5.

illuminationChange()

CV_EXPORTS_W void cv::illuminationChange	(	InputArray	src,
		InputArray	mask,
		OutputArray	dst,
		float	alpha = 0.2f,
		float	beta = 0.4f
	)

Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.

引数

src	Input 8-bit 3-channel image.
mask	Input 8-bit 1 or 3-channel image.
dst	Output image with the same size and type as src.
alpha	Value ranges between 0-2.
beta	Value ranges between 0-2.

This is useful to highlight under-exposed foreground objects or to reduce specular reflections.

seamlessClone()

CV_EXPORTS_W void cv::seamlessClone	(	InputArray	src,
		InputArray	dst,
		InputArray	mask,
		Point	p,
		OutputArray	blend,
		int	flags
	)

Image editing tasks concern either global changes (color/intensity corrections, filters, deformations) or local changes concerned to a selection. Here we are interested in achieving local changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless manner. The extent of the changes ranges from slight distortions to complete replacement by novel content [PM03] .

引数

src	Input 8-bit 3-channel image.
dst	Input 8-bit 3-channel image.
mask	Input 8-bit 1 or 3-channel image.
p	Point in dst image where object is placed.
blend	Output image with the same size and type as dst.
flags	Cloning method that could be cv::NORMAL_CLONE, cv::MIXED_CLONE or cv::MONOCHROME_TRANSFER

textureFlattening()

CV_EXPORTS_W void cv::textureFlattening	(	InputArray	src,
		InputArray	mask,
		OutputArray	dst,
		float	low_threshold = 30,
		float	high_threshold = 45,
		int	kernel_size = 3
	)

By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect. Here Canny Edge Detector is used.

引数

src	Input 8-bit 3-channel image.
mask	Input 8-bit 1 or 3-channel image.
dst	Output image with the same size and type as src.
low_threshold	Range from 0 to 100.
high_threshold	Value > 100.
kernel_size	The size of the Sobel kernel to be used.

覚え書き

The algorithm assumes that the color of the source image is close to that of the destination. This assumption means that when the colors don't match, the source image color gets tinted toward the color of the destination image.