Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Downsampling01:20

Downsampling

821
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...
821
Upsampling01:22

Upsampling

730
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...
730
Deconvolution01:20

Deconvolution

722
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
722
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

14.9K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
14.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Universal Demosaicking for Interpolation-Friendly RGBW Color Filter Arrays.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2023
Same author

CD19 targeted CAR-T therapy versus chemotherapy in re-induction treatment of refractory/relapsed acute lymphoblastic leukemia: results of a case-controlled study.

Annals of hematology·2018
Same author

Changes in dynamic functional connections with aging.

NeuroImage·2018
Same author

Knockdown of Long Non-Coding RNA RP11-445H22.4 Alleviates LPS-Induced Injuries by Regulation of MiR-301a in Osteoarthritis.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology·2018
Same author

Bi-tangent line based approach for multi-camera calibration using spheres.

Journal of the Optical Society of America. A, Optics, image science, and vision·2018
Same author

Argonaute 2 Is Required for Extra-embryonic Endoderm Differentiation of Mouse Embryonic Stem Cells.

Stem cell reports·2018
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: Apr 16, 2026

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

8.9K

Penrose demosaicking.

Chenyan Bai, Zhouchen Lin, Jian Yu

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |March 14, 2015
    PubMed
    Summary
    This summary is machine-generated.

    The Penrose pixel layout significantly improves super-resolution for color images. A novel sparse representation method enables Penrose demosaicking, outperforming traditional layouts in quality.

    More Related Videos

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
    07:12

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

    Published on: January 6, 2026

    711
    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.9K

    Related Experiment Videos

    Last Updated: Apr 16, 2026

    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

    8.9K
    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
    07:12

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

    Published on: January 6, 2026

    711
    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.9K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Digital Imaging

    Background:

    • The Penrose pixel layout, an aperiodic arrangement, shows promise for super-resolution.
    • Previous studies focused solely on grayscale images, leaving color image performance unexamined.
    • Demosaicking color images from Penrose raw data presents unique challenges due to missing color components.

    Purpose of the Study:

    • To evaluate the performance of the Penrose pixel layout for color image super-resolution.
    • To develop a demosaicking method specifically for Penrose pixel layouts.
    • To compare the Penrose layout against traditional square pixel layouts for color images.

    Main Methods:

    • Development of a sparse representation-based demosaicking algorithm for Penrose pixel layouts.
    • Reconstruction of regular color images from Penrose raw images.
    • Comparative analysis using perceptual evaluation and S-CIELAB metrics.

    Main Results:

    • The Penrose pixel layout demonstrates superior performance in color image super-resolution compared to regular layouts.
    • The proposed Penrose demosaicking method effectively reconstructs color images.
    • The Penrose layout's uniform three-colorability and simple pixel shapes (rhombi) facilitate manufacturing.

    Conclusions:

    • The Penrose pixel layout offers significant advantages for color image super-resolution.
    • Sparse representation provides an effective solution for challenging Penrose demosaicking.
    • The Penrose layout is a practical and high-performing alternative to traditional pixel arrangements.