Image Filtering and Enhancement

Contrast adjustment, morphological filtering, deblurring, ROI-based processing

Image enhancement is the process of adjusting images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or adjust the contrast of an image, making it easier to identify key features.

Categories

Image Filtering
Convolution and correlation, predefined and custom filters, nonlinear filtering, edge-preserving filters
Contrast Adjustment
Contrast adjustment, histogram equalization, decorrelation stretching
ROI-Based Processing
Define and operate on regions of interest (ROI)
Morphological Operations
Dilate, erode, reconstruct, and perform other morphological operations
Deblurring
Deconvolution for deblurring
Neighborhood and Block Processing
Define neighborhoods and blocks for filtering and I/O operations
Image Arithmetic
Add, subtract, multiply, and divide images

Featured Examples

Contrast Enhancement Techniques

Contrast Enhancement Techniques

Adjust the contrast of grayscale and color images using intensity value mapping, histogram equalization, and contrast-limited adaptive histogram equalization.

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Comparison of Auto White Balance Algorithms

Comparison of Auto White Balance Algorithms

Estimate illumination and perform white balance of a scene using three different illumination algorithms.

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Low-Light Image Enhancement

Low-Light Image Enhancement

Brighten dark regions of an image while preventing oversaturation of bright regions.

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Generate HDL Code for Image Sharpening

Generate HDL Code for Image Sharpening

Implement an FPGA-based module for image sharpening using Vision HDL Toolbox™.

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