Process digital images with computer algorithms
Digital image processing is the use of computer algorithms to create, process, communicate, and display digital images. Digital image processing algorithms can be used to:
- Convert signals from an image sensor into digital images
- Improve clarity, and remove noise and other artifacts
- Extract the size, scale, or number of objects in a scene
- Prepare images for display or printing
- Compress images for communication across a network
The following images illustrate a few of these examples:
Removing noise using a Wiener Filter.
Counting circular objects in an image.
Effective techniques for processing digital images include using algorithms and tools that provide a comprehensive environment for data analysis, visualization, and algorithm development.
For more information, see Image Processing Toolbox™.
Examples and How To
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Image Processing Toolbox Overview (2:03) - Video
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Color-Based Segmentation with Live Image Acquisition (5:11) - Video
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Applying Contrast Enhancement Techniques - Example
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Identifying Round Objects - Example
Software Reference
- Analyzing and Enhancing Images - Documentation
- Spatial Transformations - Documentation
- Image Deblurring - Documentation
- Color Image Processing - Documentation
- Morphological Operations - Documentation
- Image Processing Tool - MATLAB Apps
- Finding Circles Tool - MATLAB App
- Integrating MATLAB and C/C++
See also: Steve on Image Processing, Digital Image Processing Using MATLAB (book), image enhancement, image segmentation, image transform, image analysis, geometric transformation and image registration, image processing and computer vision, feature extraction, stereo vision, optical flow, color profile, image analysis, image thresholding, edge detection, image registration, ransac, pattern recognition, affine transformation, lab color
