Reprint

Advances in Image Enhancement

Edited by
June 2023
330 pages
  • ISBN978-3-0365-7941-2 (Hardback)
  • ISBN978-3-0365-7940-5 (PDF)

This book is a reprint of the Special Issue Advances in Image Enhancement that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Summary

In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques. The topic of advances in the image enhancement of electronics is presented in this reprint, which brings together the research accomplishments of researchers from academia and industry. The secondary goal of this reprint is to display the latest research results of advances in image enhancement.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
dual networks; enhanced CNN; fine learning block; image super-resolution; image super-resolution; attention mechanism; convolutional neural networks; deep learning; generative adversarial networks; multiple domains; translate images; restart strategy; adaptive adjustment; particle swarm optimization; spline interpolation; image denoising; GAN; optimization algorithm; autoencoder; ResNet; object detection; YOLOv5s; attention mechanism; deep learning; image segmentation; wavelet scattering; loss function; active contour; medical image; image stitching; camera calibration; layered projection; binocular ranging; stereo correction; ResNet; HOG; feature fusion; DHV recognition; image enhancement; cross stage partial network; zero-reference; Ghost module; NDT registration; map building; RandLa-Net; random sampling; semantic segmentation; capsule network; image enhancement; power line scene recognition; complex background; Visual SLAM; dynamic scene; YOLOv5; K-means clustering; probability update; side-scan sonar; segmentation; CNN; SE-block; multi-channel; blockchain technology; electronic bidding; system design; A-star algorithm; artificial potential field method; least squares method; path planning; night image dehazing; encoder–decoder architecture; image fusion; multi-scale network; serial architecture; U-net; blind watermark removal; low illumination; image enhancement; Retinex theory; histogram equalization; image fusion; image denoising; wavelet transform; color moments; non-local mean filter