correctChromaticAberration

Computational photographyfunctionOpenCV 5.0.0

import { correctChromaticAberration } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSinput_image, coefficients, output_image, image_size

FUNCTIONcorrectChromaticAberration

RETURN TYPEvoid

Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

photo_render

example: samples/cpp/snippets/chromatic_aberration_correction.cpp An example correcting chromatic aberration with C++ example: samples/python/snippets/chromatic_aberration_correction.py An example correcting chromatic aberration with Python Corrects lateral chromatic aberration in an image using polynomial distortion model.

This function loads polynomial calibration data from the specified file and applies a channel‐specific warp to remove chromatic aberration. If input_image has one channel, it is assumed to be a raw Bayer image and is first demosaiced using bayer_pattern. If it has three channels, it is treated as a BGR image and bayer_pattern is ignored.

Firstly, calibration needs to be done using apps/chromatic-aberration-calibration/ca_calibration.py on a photo of a pattern of black discs on white background, included in opencv_extra/testdata/cv/cameracalibration/chromatic_aberration/chromatic_aberration_pattern_a3.png

Calibration and correction are based on the algorithm described in [rudakova2013precise]. The chromatic aberration is modeled as a polynomial of some degree in red and blue channels compared to green. In calibration, a photo of many black discs on white background is used, and the displacements between the centres of discs in red and blue channels compared to green are minimized. The coefficients are then saved in a yaml file which can be used with this function to correct lateral chromatic aberration.

See: loadChromaticAberrationParams, demosaicing

correctChromaticAberration(input_image: Mat, coefficients: Mat, output_image: Mat, image_size: Size, calib_degree: number, bayer_pattern: number): void;

2 available overloads

correctChromaticAberration(input_image: Mat, coefficients: Mat, output_image: Mat, image_size: Size, calib_degree: number): void;

correctChromaticAberration(input_image: Mat, coefficients: Mat, output_image: Mat, image_size: Size, calib_degree: number, bayer_pattern: number): void;

input_image: Input BGR image to correct
coefficients: Coefficient model
output_image: Output destination, filled by the native operation. Corrected BGR image
image_size: Size of images for the calibration coefficient model
calib_degree: Degree of the calibration coefficient model
bayer_pattern: Bayer pattern code (e.g. cv::COLOR_BayerBG2BGR) used for demosaicing when input_image has one channel; ignored otherwise.

Upstream declaration ↗

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