[−][src]Module opencv::photo
Computational Photography
This module includes photo processing algorithms
Inpainting
Denoising
HDR imaging
This section describes high dynamic range imaging algorithms namely tonemapping, exposure alignment, camera calibration with multiple exposures and exposure fusion.
Contrast Preserving Decolorization
Useful links:
http://www.cse.cuhk.edu.hk/leojia/projects/color2gray/index.html
Seamless Cloning
Useful links:
https://www.learnopencv.com/seamless-cloning-using-opencv-python-cpp
Non-Photorealistic Rendering
Useful links:
http://www.inf.ufrgs.br/~eslgastal/DomainTransform
https://www.learnopencv.com/non-photorealistic-rendering-using-opencv-python-c/
Constants
INPAINT_NS | |
INPAINT_TELEA | |
LDR_SIZE | |
MIXED_CLONE | |
MONOCHROME_TRANSFER | |
NORMAL_CLONE | |
NORMCONV_FILTER | |
RECURS_FILTER |
Traits
AlignExposures | The base class for algorithms that align images of the same scene with different exposures |
AlignMTB | This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations. |
CalibrateCRF | The base class for camera response calibration algorithms. |
CalibrateDebevec | Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. Objective function is constructed using pixel values on the same position in all images, extra term is added to make the result smoother. |
CalibrateRobertson | Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. This algorithm uses all image pixels. |
MergeDebevec | The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response. |
MergeExposures | The base class algorithms that can merge exposure sequence to a single image. |
MergeMertens | Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids. |
MergeRobertson | The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response. |
Tonemap | Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range. |
TonemapDrago | Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain. |
TonemapMantiuk | This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid, transforms contrast values to HVS response and scales the response. After this the image is reconstructed from new contrast values. |
TonemapReinhard | This is a global tonemapping operator that models human visual system. |
Functions
color_change | Given an original color image, two differently colored versions of this image can be mixed seamlessly. |
create_align_mtb | Creates AlignMTB object |
create_calibrate_debevec | Creates CalibrateDebevec object |
create_calibrate_robertson | Creates CalibrateRobertson object |
create_merge_debevec | Creates MergeDebevec object |
create_merge_mertens | Creates MergeMertens object |
create_merge_robertson | Creates MergeRobertson object |
create_tonemap | Creates simple linear mapper with gamma correction |
create_tonemap_drago | Creates TonemapDrago object |
create_tonemap_mantiuk | Creates TonemapMantiuk object |
create_tonemap_reinhard | Creates TonemapReinhard object |
decolor | Transforms a color image to a grayscale image. It is a basic tool in digital printing, stylized black-and-white photograph rendering, and in many single channel image processing applications CL12 . |
denoise_tvl1 | Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional). As the image denoising, in particular, may be seen as the variational problem, primal-dual algorithm then can be used to perform denoising and this is exactly what is implemented. |
detail_enhance | This filter enhances the details of a particular image. |
edge_preserving_filter | Filtering is the fundamental operation in image and video processing. Edge-preserving smoothing filters are used in many different applications EM11 . |
fast_nl_means_denoising_color | Modification of fastNlMeansDenoising function for colored images |
fast_nl_means_denoising_colored_multi | Modification of fastNlMeansDenoisingMulti function for colored images sequences |
fast_nl_means_denoising_multi | Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces. For more details see http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394 |
fast_nl_means_denoising_multi_1 | Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces. For more details see http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394 |
fast_nl_means_denoising_vec | Perform image denoising using Non-local Means Denoising algorithm http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/ with several computational optimizations. Noise expected to be a gaussian white noise |
fast_nl_means_denoising_window | Perform image denoising using Non-local Means Denoising algorithm http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/ with several computational optimizations. Noise expected to be a gaussian white noise |
illumination_change | 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. |
inpaint | Restores the selected region in an image using the region neighborhood. |
pencil_sketch | Pencil-like non-photorealistic line drawing |
seamless_clone | 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 . |
stylization | Stylization aims to produce digital imagery with a wide variety of effects not focused on photorealism. Edge-aware filters are ideal for stylization, as they can abstract regions of low contrast while preserving, or enhancing, high-contrast features. |
texture_flattening | 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. |