Image Enhancement
Enhancement methods in image processing
Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further analysis. For example, you can remove noise or brighten an image, making it easier to identify key features.
You can perform image enhancement in MATLAB with Image Processing Toolbox, which provides algorithms for image enhancement, including:
- Contrast-limited adaptive histogram equalization (CLAHE)
- Decorrelation stretch
- Histogram equalization
- Linear contrast adjustment
- Median filtering
- Unsharp mask filtering
- Noise-removal Wiener filtering
Examples and How To
- Image Processing with MATLAB (Webinar)
- Image Deblurring (Blog)
- Image Contrast Enhancement Techniques (Example)
- Noise Removal with Blind Deconvolution (Example)
- Deblurring with Lucy-Richardson Algorithm (Example)
- Enhancing Multispectral Color Composite Images (Example)
Software Reference
- Analyzing and Enhancing Images (Documentation)
- Removing Noise from Images (Documentation)
- Image Enhancement and Restoration (Function List)
See also: Steve on Image Processing, image segmentation, digital image processing, image transform, image analysis, spatial transformations and image registration, image and video processing
