Advances in Image Processing, Analysis and Recognition Technology
Frejlichowski, Dariusz (editor)
For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches.
KeywordsCIELab; component Substitution; Pan sharpening; Pléiades VHR Image; coal; inertinite macerals; classification; multifractal analysis; support vector machine; block-based coding; video coding; H.265/HEVC; affine motion compensation; image registration; homography matrix; local homography transformation; convolutional neural network; moving direct linear transformation; super-resolution (SR); convolution neural network (CNN); Gene Expression Programming (GEP); deep learning; image preclassification; suspicious behavior detection; motion; magnitude; gradient; reactivity; saliency; haze removal; dark channel; atmospheric-light estimation; coarse-to-fine search strategy; sparse dictionary; stable recovery; frame; RIP; local dimming; retinex theory; bi-histogram equalization; contrast ratio; details preservation; pansharpening; image fusion; image quality; Satellite Pour l’Observation de la Terre (SPOT) 6; spectral consistency; spatial consistency; synthesis; artificial intelligence; dental application; images; detection; parseval frame; transform; sparse representation; octave convolution; bilingual scene text reading; Ethiopic script; attention; nasal cytology; automatic cell segmentation; rhinology; image analysis; feature extraction; shape context; plant recognition; DPCNN; BOF; numeral spotting; historical document analysis; convolutional neural networks; deep transfer learning; handwritten digit recognition; spectrum correction; intensity correction; compressed sensing; tradeoff process; IKONOS; remote sensing; fine-tuning; learning rate scheduler; cyclical learning rates; label smoothing; classification accuracy; neural networks; salient object detection; RGB-D; object detection; small object; multi-scale sampling; balanced sampling; texture; structure; optical; coke; iron ore; sinter; image processing; segmentation; identification; action recognition; silhouette sequences; shape features; ambient assisted living; active ageing; n/a
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Publication date and placeBasel, 2022
Information technology industries