Digital Image Processing: From Start to Finish

Are you interested in learning how digital images are processed, from the moment of their acquisition all the way through to interpretation? Join us for a detailed overview of the process.

Image Acquisition

Cameras

Sensors in digital cameras capture images. Different cameras yield varying degrees of accuracy, depending on the quality of their lenses and sensors.

Scanners

Scanners capture images. Careful calibration is required to ensure accuracy in color and resolution.

Telescopes

Telescopes capture images of space. Motors allow telescopes to track moving objects and obtain long-exposure images.

Satellites

Satellites capture images of the earth's surface. Processing is required to correct for atmospheric interference and align overlapping images.

Image Preprocessing

1

Filtering

Noise reduction, blurring, sharpening, and edge detection can all be employed in order to improve final output.

2

Color correction

Adjustment of white balance, levels, saturation, brightness, and contrast can help correct color issues introduced by capture hardware.

3

Resizing and cropping

Manipulating the size of images or cropping can be helpful before applying further processing to improve computational performance.

Image Enhancement

Histogram equalization

A technique to increase local contrast and distribute the values in the image more evenly.

Contrast stretching

Modifies the pixel intensity to expand the range of values present in the image.

Unsharp masking

A sharpening method that enhances edges after exaggerating the high-frequency components in the image.

Color manipulation

Selective color extraction, color mapping, and color balancing are techniques used to modify the hues and tones present in an image.

Image Restoration

Deblurring

Restoration of an image that appears to be out of focus and has become blurry.

Image Denoising

Removing noise from image data while preserving its quality and features.

Image Retouching and Repair

Fixing flaws such as scratches, cracks, and unwanted elements present in the image.

Image Colorization

Colorizing black and white photographs to look modern and fresh.

Image Segmentation

1

Thresholding

An image threshold is a simple binary map of light and dark pixel values used to define regions of interest.

2

Edge detection

Extracts edges of objects to identify them.

3

Clustering

A technique to partition an image into different regions based on pixel values.

4

Watershed segmentation

A method used to separate overlapping objects or identify new boundaries.

Image Recognition

Object recognition

Identification of objects present within the image data based on their shape, structure and features.

Facial Recognition

Recognition and identification of faces within images. This has various applications in security and entertainment industry.

Texture Recognition

Recognition of textures like fabrics, wood, and stone. This can help improve industrial design at large scale

Pattern Recognition

Identification of underlying patterns within image data such as spatial frequencies or orientation matching.

Image Interpretation

Medical imaging

Identifying the source of medical images, such as abnormalities or nodules, to diagnose diseases.

Climate Research

Analysis of satellite imagery to track deforestation and evaluate the effects of climate change.

Traffic Surveillance

Analysis of traffic imagery to identify violations, congestion, and safety situations.