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Learning OpenCV 3 Application Development

You're reading from  Learning OpenCV 3 Application Development

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781784391454
Pages 310 pages
Edition 1st Edition
Languages
Author (1):
Samyak Datta Samyak Datta
Profile icon Samyak Datta

Table of Contents (16) Chapters

Learning OpenCV 3 Application Development
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Laying the Foundation 2. Image Filtering 3. Image Thresholding 4. Image Histograms 5. Image Derivatives and Edge Detection 6. Face Detection Using OpenCV 7. Affine Transformations and Face Alignment 8. Feature Descriptors in OpenCV 9. Machine Learning with OpenCV Command-line Arguments in C++

Implementing Vignetting in OpenCV


Now that you know about the type of changes that a Vignette mask brings about in images, we can start to think about devising a strategy for the same and ultimately go about implementing the Vignetting operation. As we have discussed, the Vignette mask leaves the central portion of an image bright and darkens the borders in all directions as we move out of the center. Now, the input image (grayscale) that we will be dealing with will have a fixed intensity value for every pixel. What we essentially need to do is modify the value of every pixel in such a manner that the pixels in the center remain at their original intensity levels while the surrounding pixels get progressively darker as we approach the borders.

How can we bring about such a transformation? Well, one way to do that would be to multiply each pixel value with a scaling constant between 0 and 1. The pixels whose intensities need to be kept as is (the ones near the center of the image) should...

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