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Abstract Underwater imaging suffers from various challenges such as color distortion, low contrast, and reduced visibility caused by light attenuation. Addressing these issues is crucial for improving the performance of ...

Humanity currently lives in a technological era that witnesses rapid progress in multiple fields. Digital image processing is one of the modern technologies that has provided practical answers to many challenges includin...

Abstract Contrast enhancement technique is a prevalent problem in aiding interpretation of Magnetic Resonance Imaging (MRI) images. A low contrast MRI image may prove to be problematic in identifying medical problems suc...

Abstract In Digital Image Processing (DIP), image enhancement using univalent functions entails mapping pixel intensity values (gray levels) using one-to-one, invertible complex functions, frequently in the frequency dom...

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive model...

Degradation of images in ocean remote sensing is primarily due to light scattering, chromatic aberration, and stochastic noise. As a result, the quality of the image content has been significantly compromised. Most ocean...

Imaging is a vital component of the diagnostic and early detection processes for many medical disorders. However, the noise in the images can sometimes interfere with the accuracy of the diagnosis. Speckle noise, Poisson...

Abstract Quantitative analysis of fluorescence microscopy images remains a significant challenge in cytopathological assessments, as subjective interpretation and inter‐observer variability hinder reproducibility and s...

Abstract Recently, numerous lightweight image super-resolution methods with low computational complexity have been proposed, achieving a promising trade-off between reconstruction quality and efficiency. However, most ex...

Abstract Brain-computer interfaces (BCIs) were initially created to help individuals with disabilities control devices and communicate without muscle movement. Today, BCIs are used for prosthetic control, cognitive enhan...

In this study, a novel Quantum Self-Attention Neural Network for Multi-Model Aerial Image Classification (QSANN-MAIC) is proposed. The objective of this paper is to develop a high-performance learning framework capable o...

Abstract Introduction This study aimed to develop a deep learning-based system to automatically assess patient positioning compliance in chest radiographs, focusing on cervical spine visibility, scapular overlap, and cos...

On-site monitoring of iron oxide (FeO) content is crucial for ensuring product quality in the steel sintering process. However, the harsh sintering environment, characterized by nonperiodicity, high dust levels, heavy sm...

ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive me...

Low-resolution images often lack fine detail and are prone to blurring, noise, and distortions, making accurate assessment challenging. This issue becomes even more challenging for applications, such as land mapping, env...

Abstract Deep learning-based image semantic segmentation techniques have made great strides in recent years. However, they still need large amounts of finely annotated image data, and generalizing the model from known cl...

Tooth surface with early caries lesion can remineralize into sound tooth surface with early intervention. However, early caries lesion is difficult to detect and frequently goes unnoticed during clinical or radiographic ...

Abstract The transformer architecture has demonstrated significant performance in image super-resolution (SR). However, for existing Transformer-based models, there are common drawbacks. They often fall short in local fe...

To address the challenge of extracting multi-scale features from distribution line insulators in complex inspection environments—where varying scales and background interference complicate detection—this study propos...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

Infrared dim and small target detection is crucial in fields, such as military reconnaissance and remote sensing. However, due to the extremely small target size, lack of texture, and low signal-to-noise ratio, the direc...

Abstract Unlike many other fields of object detection, underwater object detection presents some unique challenges. Underwater object detection is a key technology that enables underwater robots to explore aquatic enviro...

IntroductionAccurate segmentation of retinal blood vessels is essential for the early diagnosis of ophthalmic and systemic diseases such as diabetes, hypertension, and cardiovascular disorders. However, challenges such a...