FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3163345093> ?p ?o ?g. }

• W3163345093 endingPage "13" @default.
• W3163345093 startingPage "1" @default.
• W3163345093 abstract "Hyperspectral (HS) pansharpening aims to create a pansharpened image that integrates the spatial details of the panchromatic (PAN) image and the spectral content of the HS image. In this article, we present a deep convolutional network within the mature Gaussian–Laplacian pyramid for pansharpening (LPPNet). The overall structure of LPPNet is a cascade of the Laplacian pyramid dense network with a similar structure at each pyramid level. Following the general idea of multiresolution analysis (MRA), the subband residuals of the desired HS images are extracted from the PAN image and injected into the upsampled HS image to reconstruct the high-resolution HS images level by level. Applying the mature Laplace pyramid decomposition technique to the convolution neural network (CNN) can simplify the pansharpening problem into several pyramid-level learning problems so that the pansharpening problem can be solved with a shallow CNN with fewer parameters. Specifically, the Laplacian pyramid technology is used to decompose the image into different levels that can differentiate large- and small-scale details, and each level is handled by a spatial subnetwork in a divide-and-conquer way to make the network more efficient. Experimental results show that the proposed LPPNet method performs favorably against some state-of-the-art pansharpening methods in terms of objective indexes and subjective visual appearance." @default.
• W3163345093 created "2021-05-24" @default.
• W3163345093 creator A5003831702 @default.
• W3163345093 creator A5010255725 @default.
• W3163345093 creator A5042421392 @default.
• W3163345093 creator A5044736869 @default.
• W3163345093 creator A5045803591 @default.
• W3163345093 creator A5067798266 @default.
• W3163345093 date "2022-01-01" @default.
• W3163345093 modified "2023-10-17" @default.
• W3163345093 title "Laplacian Pyramid Dense Network for Hyperspectral Pansharpening" @default.
• W3163345093 cites W1799163428 @default.
• W3163345093 cites W1885185971 @default.
• W3163345093 cites W1943127271 @default.
• W3163345093 cites W1980110630 @default.
• W3163345093 cites W1990231296 @default.
• W3163345093 cites W2001800591 @default.
• W3163345093 cites W2054440797 @default.
• W3163345093 cites W2078855750 @default.
• W3163345093 cites W2086440593 @default.
• W3163345093 cites W2100109944 @default.
• W3163345093 cites W2100329651 @default.
• W3163345093 cites W2103504761 @default.
• W3163345093 cites W2111924917 @default.
• W3163345093 cites W2121652279 @default.
• W3163345093 cites W2125008487 @default.
• W3163345093 cites W2129953395 @default.
• W3163345093 cites W2139529730 @default.
• W3163345093 cites W2144436897 @default.
• W3163345093 cites W2149720806 @default.
• W3163345093 cites W2163677711 @default.
• W3163345093 cites W2171108951 @default.
• W3163345093 cites W2171211028 @default.
• W3163345093 cites W2462592242 @default.
• W3163345093 cites W2514340250 @default.
• W3163345093 cites W2619662254 @default.
• W3163345093 cites W2767224066 @default.
• W3163345093 cites W2777033955 @default.
• W3163345093 cites W2890250462 @default.
• W3163345093 cites W2952004563 @default.
• W3163345093 cites W2963129413 @default.
• W3163345093 cites W2963446712 @default.
• W3163345093 cites W2964372277 @default.
• W3163345093 cites W2970485354 @default.
• W3163345093 cites W2988442756 @default.
• W3163345093 cites W2991454840 @default.
• W3163345093 cites W2992813042 @default.
• W3163345093 cites W3001742927 @default.
• W3163345093 cites W3097824737 @default.
• W3163345093 cites W3098542449 @default.
• W3163345093 doi "https://doi.org/10.1109/tgrs.2021.3076768" @default.
• W3163345093 hasPublicationYear "2022" @default.
• W3163345093 type Work @default.
• W3163345093 sameAs 3163345093 @default.
• W3163345093 citedByCount "20" @default.
• W3163345093 countsByYear W31633450932022 @default.
• W3163345093 countsByYear W31633450932023 @default.
• W3163345093 crossrefType "journal-article" @default.
• W3163345093 hasAuthorship W3163345093A5003831702 @default.
• W3163345093 hasAuthorship W3163345093A5010255725 @default.
• W3163345093 hasAuthorship W3163345093A5042421392 @default.
• W3163345093 hasAuthorship W3163345093A5044736869 @default.
• W3163345093 hasAuthorship W3163345093A5045803591 @default.
• W3163345093 hasAuthorship W3163345093A5067798266 @default.
• W3163345093 hasConcept C107445234 @default.
• W3163345093 hasConcept C110384440 @default.
• W3163345093 hasConcept C115961682 @default.
• W3163345093 hasConcept C121927907 @default.
• W3163345093 hasConcept C134306372 @default.
• W3163345093 hasConcept C142575187 @default.
• W3163345093 hasConcept C153180895 @default.
• W3163345093 hasConcept C154945302 @default.
• W3163345093 hasConcept C159078339 @default.
• W3163345093 hasConcept C165700671 @default.
• W3163345093 hasConcept C196216189 @default.
• W3163345093 hasConcept C205372480 @default.
• W3163345093 hasConcept C2524010 @default.
• W3163345093 hasConcept C31972630 @default.
• W3163345093 hasConcept C33923547 @default.
• W3163345093 hasConcept C41008148 @default.
• W3163345093 hasConcept C45347329 @default.
• W3163345093 hasConcept C46286280 @default.
• W3163345093 hasConcept C47432892 @default.
• W3163345093 hasConcept C50644808 @default.
• W3163345093 hasConcept C52622490 @default.
• W3163345093 hasConcept C81363708 @default.
• W3163345093 hasConceptScore W3163345093C107445234 @default.
• W3163345093 hasConceptScore W3163345093C110384440 @default.
• W3163345093 hasConceptScore W3163345093C115961682 @default.
• W3163345093 hasConceptScore W3163345093C121927907 @default.
• W3163345093 hasConceptScore W3163345093C134306372 @default.
• W3163345093 hasConceptScore W3163345093C142575187 @default.
• W3163345093 hasConceptScore W3163345093C153180895 @default.
• W3163345093 hasConceptScore W3163345093C154945302 @default.
• W3163345093 hasConceptScore W3163345093C159078339 @default.
• W3163345093 hasConceptScore W3163345093C165700671 @default.
• W3163345093 hasConceptScore W3163345093C196216189 @default.
• W3163345093 hasConceptScore W3163345093C205372480 @default.

• next