Histogram matching

Histogram matching is a technique used to transform the histogram of an image to match a specified histogram. It involves changing the pixel values of an image to achieve a desired distribution of pixel intensities. This process is also known as histogram specification and is commonly used in image processing to enhance the contrast and brightness of an image.From: A Beginner's Guide to Image Preprocessing Techniques [2018], Heart segmentation in planning CT using 2.5D U-Net++ with attention gate [2023]

Image Perfecting

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Published in Leonid P. Yaroslavsky, THEORETICAL FOUNDATIONS of DIGITAL IMAGING Using MATLAB®, 2012

Leonid P. Yaroslavsky

Algorithmically, the histogram matching can be implemented through the histogram equalization, a nonlinear transformation that converts image histograms to uniform histograms. For the histogram matching, it is sufficient to find histogram equalization transformation for the image to be transformed and that for the image with the reference histogram. The required histogram matching transformation can then be obtained by combining histogram equalization transformation for the image to be transformed and the transformation inverse to the histogram equalization transformation for the reference histogram.

Heart segmentation in planning CT using 2.5D U-Net++ with attention gate

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Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023

J. O. B. Diniz, D. A. Dias Júnior, L. B. da Cruz, G. L. F. da Silva, J. L. Ferreira, D. B. Q. Pontes, A. C. Silva, A. C. de Paiva, M. Gattas

Histogram matching is the transformation of an image so that its histogram corresponds to a specified histogram. The histogram matching can be used to balance acquisition system responses and normalise two images when different light sources have acquired images, sensors, weather or lighting (Gonzalez and Woods 2010).

Histogram matching

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Image Perfecting

Heart segmentation in planning CT using 2.5D U-Net++ with attention gate