Brightfield images of rank-based transformation (RBT)

Published: 17 April 2025| Version 1 | DOI: 10.17632/r8n2kp2m8g.1
Contributor:
Torbjörn Nordling

Description

The Rank-Based Transformation (RBT) method combines histogram expansion and normalization to enhance image contrast. It works by ranking each pixel's intensity in ascending order, and then redistributing these ranks evenly across a specified intensity range. Pixels with identical intensities share the same rank, ensuring consistent mapping. This process produces an output image with uniformly spaced intensity levels, improving contrast while preserving relative intensity relationships. For more details, please check the included README.md or visit the GitHub for RBT algorithm (https://github.com/nordlinglab/RBT).

Files

Steps to reproduce

How to Apply RBT in Your Work: For MATLAB Users, call the RBT.m function from your main script. For Python Users, call the RBT.py function from your main script. Please make sure to specify the path to your input image and the directory where you want to save the output images in your main code. For more details, please check the included README.md or visit the GitHub for RBT algorithm (https://github.com/nordlinglab/RBT).

Institutions

National Cheng Kung University

Categories

Image Enhancement

Funding

Ministry of Science and Technology

MOST 108-2811-E-006-046

Ministry of Science and Technology

MOST-109-2224-F-006-003

Ministry of Science and Technology

MOST-110-2222-E-006-010

Ministry of Science and Technology

MOST-110-2326-B-006-001-MY3

Ministry of Science and Technology

MOST-111-2221-E-006-186

Licence