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These images were manually extracted from large images from the USGS National Map Urban Area Imagery collection for various urban areas around the US. This is a 21 class land use image dataset meant for research purposes. There are 100 images for each class. 2,100 Image chips of 256x256, 30 cm (1 foot) GSD Land cover classification 2010 [171]
Test image of jelly beans from the USC-SIPI image database. A standard test image is a digital image file used across different institutions to test image processing and image compression algorithms. By using the same standard test images, different labs are able to compare results, both visually and quantitatively.
Image of Lena Forsén used in many image processing experiments. (Click on the image to access the actual 512×512px standard test version.) Lenna (or Lena) is a standard test image used in the field of digital image processing, starting in 1973. [1]
Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
Focus stacking – also called focal plane merging, z-stacking, [1] or focus blending – is a digital image processing technique which combines multiple images taken at different focus distances to give a resulting image with a greater depth of field (DOF) than any of the individual source images.
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [2] navigation of mobile robots, [3] or edge detection in images.
Visual representation of an image pyramid with 5 levels. Pyramid, or pyramid representation, is a type of multi-scale signal representation developed by the computer vision, image processing and signal processing communities, in which a signal or an image is subject to repeated smoothing and subsampling.