Advance in Digital Signal, Image and Video Processing

© 2022 by the authors; CC BY-NC-ND license

canny edge detector; deep belief network; dragonfly optimization algorithm; image processing; local binary pattern; tool wear monitoring; agile; implementation; hardware development; case study; user experience; oil sheen; oil pollution monitoring; convolutional neural network; transfer learning; traffic prediction; artificial neural networks; adaptive video; integrity analysis; integrity preservation trace; video contents; blockchain; digital video forensic; scrambled linear block codes; cross-correlation of symbols; partial autocorrelation function; convolutional long short-term memory neural networks; IMS; NGN; MPLS; call processing performance; quality of service; performance evaluation; traffic model; polar code; neural network; decoder; deblocking filter; quality assessment; parallel edge filter; HEVC/H.265; sample adaptive offset filter; nighttime dehazing; daytime dehazing; mixed-filter; high-light area transmission compensation; regularization; guided filtering; nonuniformity correction; infrared focal plan linear array detector; linear regression fitting; video quality; objective quality assessment methods; subjective quality assessment methods; user experience; user perception; QoE; video codecs; H.264 (AVC); H.265 (HEVC); VP9; network security; antivirus evasion; cybersecurity; EEG (electroencephalography); HCI (human–computer interaction); mining; occupational safety; swarm intelligence; UX (user experience); wireless networks; n/a