||Adjust image intensity values or colormap|
||Adjust Contrast tool|
||Sharpen image using unsharp masking|
||Fast Local Laplacian Filtering of images|
||Edge-aware local contrast manipulation of images|
||Render HDR image for viewing while enhancing local contrast|
||Enhance contrast using histogram equalization|
||Contrast-limited adaptive histogram equalization (CLAHE)|
||Adjust histogram of image to match N-bin histogram of reference image|
||Apply decorrelation stretch to multichannel image|
||Find limits to contrast stretch image|
||Convert integer values using lookup table|
||Add noise to image|
Using the Image Viewer's Adjust Contrast tool
This example shows how to increase the contrast in a low-contrast grayscale image by remapping the data values to fill the entire available intensity range [0, 255].
The process of adjusting intensity values can be done automatically using histogram equalization.
As an alternative to using
histeq, you can
perform contrast-limited adaptive histogram equalization (CLAHE) using
Decorrelation stretching enhances the color separation of an image with significant band-to-band correlation.
Image enhancement techniques are used to improve an image, where "improve" is sometimes defined objectively (e.g., increase the signal-to-noise ratio), and sometimes subjectively (e.g., make certain features easier to see by modifying the colors or intensities).
An image lacks contrast when there are no sharp differences between black and white.