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27 articles for “Super resolution”
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Reconstruction Techniques for Super Resolution Using Low Resolution Images
Abstract: The aim of Super Resolution (SR) reconstruction is to restore High Resolution (HR) image using information obtained from many degraded and aliased Low Resolution (LR) images. SR is signal processing for bandwidth expansion beyond the pass band of the imaging hardware system by using spatio-temporal information available from LR images. Over last three-decade various researchers contributed in the field of SR, but all are intuitive SR mechanisms. This paper employs …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 2, 2021 · pp. 5–13 Read article
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Zoom Based Image Super-Resolution: Using Two Level DWT as Feature Model
Abstract: AbstractIn this paper we present an algorithm of super-resolution (SR) imaging to reconstruct high-resolution (HR) image from sequence of low-resolution (LR) images of static scene captured at the different camera zoom factor. The resultant HR image is constructed at the resolution of the most zoomed LR image. In the proposed approach algorithm uses LR images of the static scene captured at three distinct zoom-factors. Learning based SR technique is used …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 95–105 Read article
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Image Enhancement Using Super Resolution Technique
Abstract: AbstractThe proposed super resolution technique finds it’s applicability in reconstructing a distorted image to a higher resolution image. The photographs consisting of the previous techniques were drawn towards lower force light which was considered to be a huge disadvantage. In view of this default, a novel strategy of Histogram. Equalisation is introduced and further detailed investigation is carried on. Light Enlightenment and picture quality is improved using the proposed technique. …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 12–16 Read article
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Enhancing Resolution of Artifact Image using AR-CNN and SRGAN
Abstract: Abstract The super-resolution strategy recreates a higher-resolution image or arrangement from the observed low resolutions (LR) images. As super-resolution has been created for over three decades, both multi-casing and single-outline super-resolution has critical applications in our everyday life. Existing super-resolution strategies have a few constraints. The artifact is additionally an issue in compression of an image. With artifacts, the high-resolution image is most noticeably terrible to see. In this paper, …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 3, 2020 · pp. 12–19 Read article
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Inpainting an Image based on Enhanced Resolution
Abstract: AbstractInpainting is the measure of reconstructing damaged parts of images. The main goal of inpainting is to remove unwanted objects from images and fill this region with the background. At first a part of the input image is inpainted by a non-parametric patch sampling. The inpainted part of the input image allows reducing the computational complexity and less sensitive to noise. The advantage is it is easier to inpaint low …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 1, 2015 · pp. 23–26 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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The Impact of Using High-Resolution Satellite Images on Improving Geographic Maps
Abstract: By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates. The main goal is to assess which satellite imagery sources—SuperView, Ikonos, QuickBird, and WorldView—are appropriate for updating maps at 1:2500 and 1:5000 scales. The process entails evaluating radiometric quality, geometric dependability, spatial correctness, and picture resolution and comparing the results to the specifications of different mapping tasks. …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 36–44 Read article
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CBCT: A Boon in Periodontics – A Review
Abstract: Periodontal disease is an inflammatory disease that can be diagnosed mainly based on clinical signs and symptoms. Two-dimensional radiographs are valuable diagnostic tools as an adjunct to the clinical examination in assessing periodontal bone level. Two-dimensional images do not provide accurate bone levels due to its limitations like projection geometry, superimposition of adjacent anatomic structures, leading to the need for three-dimensional imaging that overcomes these limitations. The diagnosis and treatment …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 7–13 Read article
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Review on CBIR Image Based on Colour, Texture and Shape Features of Biomedical Image Applications
Abstract: This study seeks to understand how different image enhancing methods affect the sensitivity of contrast-based textural measures and morphological traits derived from high-resolution satellite data (three-band SPOT-5). The built-up/non-built-up detection framework is the backbone of every biomedical application. Using supervised learning while working with a low-resolution reference layer reduces uncertainty and boosts the reference layer's quality in a roundabout way. The image's histogram is recalculated based on contrast in order …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 8–13 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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Comparative Analysis of the Structural Integrity and Dimensional Stability of Additively Manufactured Biopolymers vs. Thermoformed PETG: A 1-Year Retrospective Study on Polymer Performance in Orthodontic Applications
Abstract: Objective: This study aimed to evaluate the long-term dimensional accuracy and structural performance of direct 3D-printed biopolymers compared to conventional vacuum-formed Polyethylene Terephthalate Glycol (PETG) composites. The investigation focused on how different polymer processing methods (additive manufacturing vs. thermoforming) influence material thinning and resistance to occlusal stress. Methods: A retrospective analysis was conducted on 60 cases (n = 60) of post-orthodontic maintenance. The sample was divided into two cohorts: Group …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 140–146 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 45–61 Read article
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Fabrication, Interfacial Characterization, and Superparamagnetic Properties of Fe₃O₄@γ-Fe₂O₃ Core/Shell Nanoparticle-Reinforced Chitosan Biopolymer Composites
Abstract: Magnetite/maghemite core/shell nanoparticles were prepared by alkaline co-precipitation of Fe(II) and Fe(III) precursors followed by controlled thermal oxidation at 350 °C and subsequently incorporated into chitosan at 1, 3, and 5 wt% loadings by solution casting. The resulting films were evaluated by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), high-resolution transmission electron microscopy (HR-TEM), vibrating-sample magnetometry (VSM), thermogravimetric analysis (TGA), and tensile testing. XRD showed the characteristic cubic spinel reflections …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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X-ray Telescopes: Technological Developments and Contributions to High-Energy Astrophysics
Abstract: X-ray telescopes have revolutionized our understanding of the high-energy universe, unveiling phenomena that are invisible to optical telescopes. This paper reviews the technological advancements in X-ray telescope design, instrumentation, and data analysis techniques, which have significantly enhanced their sensitivity and resolution. We trace the development from early X-ray detectors to modern space-based observatories like the Chandra X-ray Observatory and the XMM-Newton. These advancements have facilitated groundbreaking discoveries, such as the …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article