26 papers · ranked by Valyu relevance
Muhammad Nouman Noor, Muhammad Masab, Farah Haneef, Muzammil Hussain + 4 more
The spread of plant diseases in important crops that influence the economy, particularly in Asia, such as tomatoes, coffee, cucumbers, olives, and wheat, poses a serious threat to agricultural production and global food security. Traditional detection methods are frequently labor-intensive, slow, and lack the public…
Jorge Luis Beltran Diaz, Jan G. Korvink, Danays Kunka
Despite the growing interest in multicontrast X-ray imaging, spatial harmonic imaging remains limited by a lack of specialized computational resources. In this paper, we present SHI, a high-performance software framework that covers the range from data acquisition to processing in spatial harmonic imaging experiments.…
Mohammad, Noor Islam S.
—This study introduces a modular framework for spatial image processing, integrating grayscale quantization, color and brightness enhancement, image sharpening, bidirectional transformation pipelines, and geometric feature extraction. A stepwise intensity transformation quantizes grayscale images into eight discrete…
Aishwarya Makam, Vishnu Ramadas, Anly Tollan, Ishan Bhattacharyya + 2 more
Title: Summary Investigating exocytosis in human pancreatic islet cells is challenging due to small vesicle size and variable imaging parameters. Here, we present a protocol to detect and analyze exocytosis with an image-processing algorithm using Lagrangian particle tracking. We describe steps for sample preparation…
Pegah Dehbozorgi, Oleg Ryabchykov, Thomas W. Bocklitz
As medical imagery remains the cornerstone of diagnosis, the success of complex classification tasks depends on high-quality data and diagnostic features. This study evaluates image pre-processing and feature extraction to optimize model performance. Our investigation assesses how variations in pre-processing and…
Chutia, Rupjyoti, Bora, Dibya Jyoti
The systematic and meticulous handling and processing of digital images through use of advanced computer algorithms is popularly known as the digital image processing. It has received significant attention in both academic and practical fields. Image enhancement serves as a crucial preprocessing stage in each of the…
Lei Xu, Mohsen Rahmani
Arrays of resonant nanoparticles, so-called metasurfaces, have been developed and demonstrated as the first generation of meta-operators. Unlike today’s electronic systems, the demonstrated compact, scalable platform enables ultrafast, energy-efficient all-optical image processing, extending to holographic wavefront…
Nhat Thanh Tran, Kevin Bui, Jack Xin
Image smoothing is a fundamental image processing operation that preserves the underlying structure, such as strong edges and contours, and removes minor details and textures in an image. Many image smoothing algorithms rely on computing local window statistics or solving an optimization problem. Recent…
Soundes Oumaima Boufaida, Abdemadjid Benmachiche, Majda Maâtallah
Embedded vision systems need efficient and robust image processing algorithms to perform real-time, with resource-constrained hardware. This research investigates image processing algorithms, specifically edge detection, corner detection, and blob detection, that are implemented on embedded processors, including DSPs…
Justin Downes, Sam Saltwick, Anthony Chen
The compression of satellite imagery remains an important research area as hundreds of terabytes of images are collected every day, which drives up storage and bandwidth costs. Although progress has been made in increasing the resolution of these satellite images, many downstream tasks are only interested in small…
Alexey Terekhov, Ravil I. Mukhamediev, Igor Savin, Donald Bailey
The thematic processing of pseudocolor composite images, especially those created from remote sensing data, is of considerable interest. The set of spectral classes comprising such images is typically described by a nominal scale, meaning the absence of any predetermined relationships between the classes. However, in…
Ong, D. Chee Yong, Bukhori, I. + 4 more
Scanning Electron Microscopy (SEM) images often suffer from noise contamination, which degrades image quality and affects further analysis. This research presents a complete approach to estimate their Signal-to-Noise Ratio (SNR) and noise variance (NV), and enhance image quality using NV-guided Wiener filter. The main…
Amish Patel, Xingjian Zhong, Mallory Moffett, Yidan Sun + 1 more
While shortwave infrared (SWIR) imaging provides superior tissue penetration and reduced autofluorescence for preclinical applications, quantitative fluorescence analysis is hindered by the limited dynamic range of InGaAs cameras, forcing a focus on either bright or dim anatomical features. We develop a high dynamic…
Stella Woeltjen, Molly Hanlon, Keely Brown, Haley Schuhl + 2 more
The lack of low-cost, user-friendly and expedient methods for plant phenotyping challenges researchers’ ability to efficiently collect accurate phenotypic data in large field experiments. Here, we demonstrate the use of a novel, smartphone-based image capture system and two user-friendly image analysis pipelines…
Roopdeep Kaur, Gour Karmakar, Muhammad Imran
Filtering noise is a fundamental part of data preparation that enhances image quality for applications such as object segmentation, detection, and recognition. Various noise reduction techniques are proposed in the literature, including the use of median, Gaussian, and bilateral filters. Convolutional neural networks…
Zhiping Xu, Deyin Xu, Yisong He, Lixiong Lin + 2 more
Synthetic Aperture Sonar (SAS) imaging technology is wildly used in the underwater applications. In the work process of SAS imaging, filtering technologies are important for SAS imaging, which can suppress different noises to improve signal quality. However, the existing filtering methods face many challenges, such as…
Douglas Dziedzorm Agbeve, Aditya V. Handrale, Salim Fares, Seif E. Idani
To better understand Martian Surface, which is needed to enable Rovers navigate Mars with ease, it is necessary to be able to determine the location of mounds. Detecting and studying these morphologies can also help us find evidence of extraterrestrial life, in this case, more specifically, water or signs of life…
Yoko Bekku, Stephen Cai, Thomas Xin, Joseph Sall + 3 more
The g-ratio, calculated as the axon diameter divided by the total myelinated fiber diameter, is widely used to assess the degree of myelination in the central and peripheral nervous systems. Changes in g-ratios accompany demyelinating, hypomyelinating, and remyelinating conditions, and can also result from…
Authors not listed
Localized detection of hydrogen permeation in steel membranes is crucial for practical applications but remains challenging. We present a reflective microscopy (RM) approach combined with machine learning (ML)-driven image analysis to address this issue. Hydrogen permeation in press-hardened steel alters the…
David H. Shtengel, Gleb Shtengel, C. Shan Xu, Harald F. Hess
Electron Microscopy (EM) is widely used in many scientific fields, particularly in life sciences, offering high-resolution information on the ultrastructure of biological organisms. Accurate characterization of EM image quality is important for assessing the EM tool performance, in addition to sample preparation…
Gail McConnell
Microscopy datasets are often spatially sparse, wherein relevant structures occupy only a small fraction of the total field of view (FOV), leaving large regions of background devoid of signal. This inherent inefficiency creates file sizes that are larger than needed, which increases the time needed for computational…
Haohong Gan, Shiyi Peng, Hailian Hu, Xuan You + 4 more
The resolving power of optical microscopy is fundamentally constrained by the diffraction of light, limiting our ability to visualize subcellular structures. Computational methods, particularly deconvolution, can restore blurred images but critically depend on an accurate point spread function (PSF), whose estimation…
Authors not listed
Understanding how plants respond to dynamic and spatially variable stimuli is a key goal in plant sciences. Traditional imaging methods often involve a trade-off between environmental control and spatial resolution, limiting their ability to capture real-time responses in high resolution. Microfluidic technology…
Authors not listed
Photocatalytic overall water splitting is a promising pathway to green hydrogen but also presents unique research challenges due to the need to detect both gaseous products (H2 and O2). While gas chromatography (GC) is the most commonly employed method in this context, it faces multiple shortcomings: low time…
Authors not listed
We present a mechanistic framework to characterize photon absorption in quantum dots, enabling rational optimization of image sensor designs. Our analysis is based on the Analytic Path structured-field model, which treats both electrons and photons as extended electromagnetic structures rather than point particles.…
Authors not listed
The capacity to pattern biomolecules within microfluidic devices expands the scope of microfluidic technologies. In such patterned systems, surface-bound components remained localized, while the microfluidic network supplies reagents and removes waste products. This approach has enabled continuous protein expression…