Digital Image Processing of Remote-Sensed Data
(book excerpts)Digital image processing refers to the manipulation and analysis of digital images using algorithms to enhance the quality of images, extract meaningful information from images, and automate image-based tasks. In general, using raw images directly acquired from remote or ground-based sensors is not suggested because the data have to be corrected due to deformations from interactions between sensors, atmospheric conditions, and terrain profiles. Digital image processing can improve visual quality, selectively enhance and highlight particular image features, and classify, identify, and extract spectral and spatial patterns representing different phenomena from images. It can also arbitrarily change image geometry and illumination conditions to give different views of the same image. Image processing cannot increase any information from the original image data. However, it can optimize the visualization to view more information from the enhanced images than from the original. Several image processing software systems have been developed specifically for remote and ground-based imaging. Government agencies and private companies that sell remotely sensed data often offer data correction services. Note that digital image processing is usually performed before geographical information system analysis (GIS).
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Topics Within This Chapter:
- Structure of Digital Images
- Photograph Versus Digital Images
- Digital Image Display
- Monochromatic Display
- False Color Composites
- Bit Depth
- Digital Image Formats
- Digital Image Preprocessing
- Radiometric Correction
- Geometric Correction
- Selection of Geometric Correction Method
- Spatial Interpolation
- Intensity Interpolation (Resampling)
- Georeferencing
- Orthorectification
- Image Registration
- Image Mosaicing
- Digital Image Enhancement
- Contrast Stretching
- Linear Contrast Stretch
- Non-Linear Contrast Stretch
- Intensity, Hue, and Saturation Transformations
- Density Slicing
- Spatial Filtering
- Digital Image Transformation
- Image Transformation Techniques
- Band Ratioing
- Vegetative Indices
- Image Fusion
- Color Space Transformations
- Principal Component Analysis
- Tasseled Cap Transformation
- Texture and Frequency-Based Transforms
- Digital Image Segmentation
- Image Segmentation Techniques
- Pixel-Based
- Object-Based
- Machine Learning
- Deep Learning
- Digital Image Classification
- Types of Image Classification
- Supervised Classification
- Unsupervised Classification
- Object-Based Image Classification
- Pixel-Based Image Classification
- Machine Learning Classification
- Deep Learning Classification
- Digital Image Processing Software Programs
