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 Experiment Video

Updated: Jun 21, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Deep homography-based image stitching with enhanced small object detection.

Jicheng Cong1, Xiaotian Ran2, Chunbin Qin3

  • 1School of Animation, Huanghuai University, Zhumadian, 463000, Henan, China.

Scientific Reports
|June 19, 2026
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

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

Sort by
Same author

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems.

Entropy (Basel, Switzerland)·2023
Same author

Critic Learning-Based Safe Optimal Control for Nonlinear Systems with Asymmetric Input Constraints and Unmatched Disturbances.

Entropy (Basel, Switzerland)·2023
Same author

A Clustering Scheme Based on the Binary Whale Optimization Algorithm in FANET.

Entropy (Basel, Switzerland)·2023
Same author

Robust Trajectory Tracking Control for Continuous-Time Nonlinear Systems with State Constraints and Uncertain Disturbances.

Entropy (Basel, Switzerland)·2022
Same journal

Integrated multi-assessment and structural performance index framework for stacking-sequence optimisation of natural fibre reinforced laminates.

Scientific reports·2026
Same journal

SuperiorGAT: graph attention networks for sparse LiDAR point cloud reconstruction in autonomous systems.

Scientific reports·2026
Same journal

The effect of stretching the pectoralis major, sternocleidomastoid, and iliopsoas muscles on 800 m swimming performance in master swimmers.

Scientific reports·2026
Same journal

ISNR-PQC: isometry noise resilience post quantum cryptography primitive.

Scientific reports·2026
Same journal

Identification of high-yielding and stable genotypes of barley in the cold climate of Iran using AMMI and GGE biplot models.

Scientific reports·2026
Same journal

Bayesian negative binomial modelling of spatial and temporal patterns of road traffic deaths in Ghana.

Scientific reports·2026
See all related articles

This study introduces a new image stitching method using YOLOv8 for better small object detection and complex backgrounds. The approach enhances feature extraction and deep homography estimation, significantly improving stitching accuracy and visual continuity.

Area of Science:

  • Computer Vision
  • Deep Learning
  • Image Processing

Background:

  • Traditional image stitching methods struggle with small objects and complex backgrounds.
  • Limitations include reduced accuracy and visual artifacts in challenging image conditions.

Purpose of the Study:

  • To develop a novel image stitching methodology overcoming limitations of traditional techniques.
  • To enhance small object detection and improve feature alignment in complex scenes.

Main Methods:

  • Leveraging YOLOv8 as a feature extractor with low-resolution feature map enhancement.
  • Utilizing multi-scale feature extraction with Spatial Pyramid Pooling.
  • Implementing a deep learning-based homography estimation module with a weighted loss function.

Related Experiment Videos

Last Updated: Jun 21, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Main Results:

  • Achieved higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) on UDIS and MVS-Synth datasets.
  • Demonstrated reduced model size (188 MB) and computational complexity (14.5 GFLOPs).
  • Ablation studies confirmed the effectiveness of individual modules.

Conclusions:

  • The proposed YOLOv8-based image stitching method significantly improves accuracy and efficiency.
  • The approach effectively handles small objects and complex backgrounds, reducing stitching artifacts.
  • Future work aims to extend the model for real-time applications in dynamic environments.