Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Upsampling01:22

Upsampling

309
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
309
Downsampling01:20

Downsampling

251
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
251
Aliasing01:18

Aliasing

224
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
224
Bandpass Sampling01:17

Bandpass Sampling

261
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
261
Sampling Theorem01:15

Sampling Theorem

760
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
760
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

131
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
131

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Programmed Cell Death in Chronic Rhinosinusitis.

Clinical and translational allergy·2026
Same author

Pressure-Induced Controllable Multicolor Emission in Ethyl 7-hydroxy-2-oxo-2H-chromene-3-carboxylate.

Chemphyschem : a European journal of chemical physics and physical chemistry·2026
Same author

A multi-branched EMS mutant of Isodon lophanthoides var. graciliflorus exhibits significant differences in phytohormones and diterpenoids.

BMC plant biology·2026
Same author

Molecular Mechanisms of Juvenile Nasopharyngeal Angiofibroma: A Narrative Review.

Current oncology (Toronto, Ont.)·2026
Same author

Intrinsic distributed sensing using wavelength-multiplexed QPSK signals in fiber-optic communication.

Optics express·2026
Same author

Warm-start or cold-start? A comparison of generalizability in gradient-based hyperparameter tuning.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026
関連記事をすべて見る

関連する実験動画

Updated: Sep 9, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K

パンシャーピングのための空間周波数領域アグレグレーションアップサンプリング

Yilong Liu1, Kai Sun2, Yuan Liu1

  • 1School of Mathematics, Northwest University, 229 North Taibai Road, Xi'an, Shaanxi, 710069, China.

Neural networks : the official journal of the International Neural Network Society
|August 30, 2025
PubMed
まとめ
この要約は機械生成です。

リモートセンシング画像の品質を向上させるため,新しい空間周波数領域集積アップサンプリング (SFAU) メソッドを導入します. SFAUは,空間情報とスペクトルの情報をよりよく融合させることで,既存のアップサンプリング技術を上回ります.

キーワード:
パンシャープ空間周波数領域アップサンプリング

さらに関連する動画

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

491
Super-resolution Imaging of Neuronal Dense-core Vesicles
09:30

Super-resolution Imaging of Neuronal Dense-core Vesicles

Published on: July 2, 2014

9.8K

関連する実験動画

Last Updated: Sep 9, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

491
Super-resolution Imaging of Neuronal Dense-core Vesicles
09:30

Super-resolution Imaging of Neuronal Dense-core Vesicles

Published on: July 2, 2014

9.8K

科学分野:

  • リモートセンシング
  • 画像処理
  • コンピュータ・ビジョン

背景:

  • パンクロマティック (PAN) と低解像度マルチスペクトル (LRMS) のデータを融合させることで,遠隔感知画像の質を向上させるには,パンシャープニングが不可欠です.
  • パンシャープングにおける画像アップサンプリングのための現在のディープラーニング方法は,PAN情報を利用し,スペクトル空間的な詳細をバランスすることに制限があります.

研究 の 目的:

  • 既存のパンシャーピングアップサンプリングの限界に対処するために,新しい空間周波数領域集積アップサンプリング (SFAU) 方法を提案する.
  • 空間情報とスペクトル情報の融合を改善し,リモートセンシング画像の品質を向上させる.

主な方法:

  • 提案されたSFAU方法は3つのモジュールで構成されています. 二重ドメイン非線形融合 (DDNF), 地域特有の注意力メカニズム (RSAM), 適応特性の融合ゲート (AFFG).
  • DDNFは,周波数認識特征集積 (FAFA) と高周波特征のキャプチャと詳細の精錬のための空間領域の強化を統合しています.
  • RSAMは特性を適応的に精製し,空間-スペクトルの相関性を保ち,AFFGは融合した情報をバランスします.

主要な成果:

  • SFAU方法は,既存のアップサンプリング技術と比較して優れた性能を示した.
  • 特に高コントラストとスペクトル的に複雑な領域で,SFAUと統合された際の主要なパンシャープングモデルでは,性能の有意な改善が観察されました.
  • このアプローチは,現実世界の遠隔感知シナリオで強力な汎用性を示した.

結論:

  • SFAU 方法は,パンシャーピングにおける現在のアップサンプリング技術の限界を効果的に解決します.
  • この新しいアプローチは,空間情報とスペクトルのバランスの取れた統合を提供し,リモートセンシング画像の品質を向上させます.
  • SFAUは,リモートセンシングの画像強化における実用的な応用の可能性を顕著に示しています.