Explore MATLAB source code curated for "图像灰度变换" with clean implementations, documentation, and examples.
Implementing image grayscale transformation in MATLAB to analyze the impact of various transformation methods on final image outcomes, with code-based demonstrations of key algorithms and functions.
Several programs for image grayscale transformations, including image color inversion, logarithmic grayscale transformation, exponential grayscale transformation, linear grayscale transformation, grayscale slicing, and image averaging for noise reduction. These programs demonstrate key algorithms for manipulating pixel intensity values to achieve various image enhancement effects.
Implementation of image processing techniques including: (1) histogram equalization, (2) histogram matching, (3) neighborhood averaging, (4) local enhancement, and (5) median filtering. Complete source code provided for these fundamental image processing operations.
Perform addition, subtraction, multiplication, and division operations on two distinct images; utilize the imadjust function for grayscale transformation; conduct additive noise removal experiments; implement grayscale transformation using linear transformation formulas and master histogram analysis for image processing