sensors-logo

Journal Browser

Journal Browser

Sensor-Based Image Processing and Sensing Techniques for Enhanced Object Detection

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 487

Special Issue Editor

Special Issue Information

Dear Colleagues,

Object detection is a fundamental task in computer vision and image understanding, playing a critical role in a wide range of applications such as autonomous driving, intelligent surveillance, medical imaging, robotics, remote sensing, and industrial inspection. In recent years, rapid advances in image processing techniques—together with deep learning, multimodal data fusion, and edge intelligence—have significantly improved the accuracy, robustness, and efficiency of object detection systems.

Despite these advances, object detection in complex real-world environments remains challenging due to factors such as occlusion, illumination variation, background clutter, scale variation, noise, and limited computational resources. Advanced image processing methods continue to be essential for enhancing detection performance, improving generalization, and enabling real-time and resource-efficient deployment.

This Special Issue aims to bring together high-quality research contributions that explore novel image processing techniques and frameworks for enhanced object detection, from theoretical foundations to practical applications.

Dr. Hao Luo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced image preprocessing and enhancement techniques for object detection
  • feature extraction, representation, and selection methods
  • image segmentation and region proposal techniques
  • deep learning-based object detection models and architectures
  • lightweight and efficient detection algorithms for edge and embedded systems
  • multi-scale, multi-view, and multi-modal object detection
  • robust object detection under challenging conditions (e.g., low light, noise, occlusion)
  • image fusion techniques for enhanced detection performance
  • object detection in medical, industrial, remote sensing, and autonomous systems
  • real-time and low-latency image processing for detection tasks
  • explainable and interpretable image processing methods for object detection
  • benchmark datasets, evaluation metrics, and comparative studies

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

29 pages, 183767 KB  
Article
An Underwater Polarization Image Fusion Algorithm Based on Information Entropy and a Hierarchical-Adaptive Fusion Framework
by Fuqiang Wang, Wei He, Shanwei Ye, Ang Ma, Xichuan Zhou, Zonghuan Guo, Jianchao Wang, Lin Zhou and Yingcheng Lin
Sensors 2026, 26(10), 3231; https://doi.org/10.3390/s26103231 - 20 May 2026
Viewed by 213
Abstract
Underwater images often exhibit low contrast and loss of detail due to light scattering and absorption, which poses significant challenges for visual analysis in aquatic environments. Polarization imaging addresses these issues by exploiting the polarization states of light, effectively reducing backscatter and enhancing [...] Read more.
Underwater images often exhibit low contrast and loss of detail due to light scattering and absorption, which poses significant challenges for visual analysis in aquatic environments. Polarization imaging addresses these issues by exploiting the polarization states of light, effectively reducing backscatter and enhancing image contrast. In this paper, we propose a polarization image fusion method guided by information entropy and a hierarchical-adaptive fusion strategy. Local information entropy is first employed to perform multiscale denoising on Degree of Linear Polarization (DOLP) images, enabling adaptive detail reconstruction while distinguishing texture from noise. Subsequently, a hierarchical fusion framework is applied: low-frequency components are enhanced through detail injection, while high-frequency components are fused using a structure-guided mechanism that leverages low-frequency gradient information to generate soft masks for phase-aligned detail integration and edge sharpening. Experiments conducted on self-collected underwater images, two public underwater datasets, and three general-scene datasets demonstrate that the proposed method improves objective metrics, including information entropy, average gradient, and edge strength. Subjective evaluations further confirm its effectiveness in preserving details and adapting to diverse scenes. Furthermore, rigorous ablation studies and runtime analyses demonstrate that the optimized framework achieves a highly favorable balance between robust, artifact-free detail enhancement and computational efficiency. The proposed approach provides a practical solution for underwater image enhancement, with potential applications in target detection and infrastructure inspection. Full article
Show Figures

Figure 1

Back to TopTop