ArticleEntropy (Basel, Switzerland)2019
Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform.
Article in Entropy (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Improved 3D reconstruction pipeline for enhancing the quality of 3D model generation from multi-view images.Scientific reports · 2025Article
- Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set.Scientific reports · 2025Article
- Improvement of medical images with multi-objective genetic algorithm and adaptive morphological transformations.Scientific reports · 2025Article
- Experimental assessment of damage and microplastic release during cyclic loading of clear aligners.PloS one · 2025Article
- Advanced enhancement technique for infrared images of wind turbine blades utilizing adaptive difference multi-scale top-hat transformation.Scientific reports · 2024Article
- Novel Entropy for Enhanced Thermal Imaging and Uncertainty Quantification.Entropy (Basel, Switzerland) · 2024Article
- Fusion of UAV-based infrared and visible images for thermal leakage map generation of building facades.Heliyon · 2023Article
- Prediction model for knee osteoarthritis using magnetic resonance-based radiomic features from the infrapatellar fat pad: data from the osteoarthritis initiative.Quantitative imaging in medicine and surgery · 2023Article
- Differential diagnosis of thyroid nodule capsules using random forest guided selection of image features.Scientific reports · 2022Article
- Image Enhancement of Maritime Infrared Targets Based on Scene Discrimination.Sensors (Basel, Switzerland) · 2022Article
- Infer Thermal Information from Visual Information: A Cross Imaging Modality Edge Learning (CIMEL) Framework.Sensors (Basel, Switzerland) · 2021Article
- Two-Dimensional EspEn: A New Approach to Analyze Image Texture by Irregularity.Entropy (Basel, Switzerland) · 2021Article
- Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology.Sensors (Basel, Switzerland) · 2021Article
- Entropy in Image Analysis.Entropy (Basel, Switzerland) · 2019Article
- Efficacy of Combination Neoadjuvant Chemotherapy and Regional Inductive Moderate Hyperthermia in the Treatment of Patients With Locally Advanced Breast Cancer.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception. These problems can be caused by variations of the environment or by limitations of the cameras that capture the images. In this work we propose a method that improves the details of infrared images, increasing their entropy, preserving their natural appearance, and enhancing contrast. The proposed method extracts multiple features of brightness and darkness from the infrared image. This is done by means of the multiscale top-hat transform. To improve the infrared image, multiple scales are added to the bright areas and multiple areas of darkness are subtracted. The method was tested with 450 infrared thermal images from a public database. Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.