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121 articles for “image de-noising”
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Image Compression via Non-separable Discrete Fractional Fourier Transform
Abstract: The main idea behind image compression is to reduce the bandwidth for transmission and required space for storage. Thus, image compression is of great importance. In this paper we present the image compression technique using Non-Separable Discrete Fractional Fourier Transform (NSDFrFT). Numerical simulation results suggested that image compression method using NSDFrFT as transform technique gives better performance for images when compression ratio is high in comparison to DFrFT and JPEG. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 3, 2015 · pp. 1–9 Read article
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Multispectral Image Denoising using Bi-Directional Recurrent Neural Network with DPCA Algorithm
Abstract: In practices, a Multispectral Images (MSI) image is always prone to corruption by various sources of noises while procuring the images. In this paper we implemented Decomposable Pixel Component Analysis (DPCA) algorithm with recurrent neural network (RNN) which effectively denoised the MSI images. The RNN enables shrinkage of non-reusable data points during DPCA execution and aid it to effectively transform spatial coordinate in a logical manner and reduces the time …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 25–30 Read article
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Image Denoising and Various Techniques: Survey
Abstract: Whenever an image is formed, various factors like lightning which includes its source, distance, intensity, and the camera characteristics, which included the sensor responses, lenses, and so on, affect the overall appearance of the image. The noise is one of the key components in this. It is important to remove noise in such a way that the overall quality is maintained and there is no loss of image information. There …
Published in Current Trends in Information Technology · Vol. 12, Issue 3, 2022 · pp. 6–11 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 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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Image Enhancement Techniques for Digital Images
Abstract: In image processing, image enhancement is a challenging problem. Image enhancement aims to process an image in a way that makes the final product better suited for a particular application than the original. There are numerous ways to improve the quality of images using digital image enhancement techniques. It is crucial to use these techniques correctly. Image enhancement is a critical aspect of image processing, focusing on improving the visual …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 14–18 Read article
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Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature
Abstract: This paper deals with secure person identification system using Back-Propagation learning neural network algorithm where appearance based facial feature and Principal Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face detector, Stam’s method of Active Shape Model has applied for detecting the facial edges and image pre-processing method has used for eliminating the background noises. For …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 26–34 Read article
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Pedestrian Gait Parameter Measurement Using a Cascade of Edge and Corner Detection Technique
Abstract: ABSTRACTMost modern surveillance systems currently rely upon Closed Circuit TV feeds monitoring system. This report documents a new approach towards automating pedestrian recognition within typical video footage. The proposed work shows how the gait parameters can be measured from the video footage using the mathematical theory of Geometry and computer vision and pattern recognition technique which can be further used for recognize individuals. When people walk normal to the viewing …
Published in Journal of Computer Technology & Applications · Vol. 1, Issue 1-3, 2011 · pp. 75–88 Read article
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Image Compression via Non-separable Discrete Fractional Fourier Transform
Abstract: The main idea behind image compression is to reduce the bandwidth for transmission and required space for storage. Thus, image compression is of great importance. In this paper we present the image compression technique using Non-Separable Discrete Fractional Fourier Transform (NSDFrFT). Numerical simulation results suggested that image compression method using NSDFrFT as transform technique gives better performance for images when compression ratio is high in comparison to DFrFT and JPEG. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 3, 2015 · pp. 1–9 Read article
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Optimization of Artifact Free Image Upscaling Using Genetic Algorithm
Abstract: Creating an upscaled image from a low-resolution (LR) image to high resolution (HR) is very interesting. The nature and texture of an image should be maintained during upscaling of an image. This upscaling is also termed as “super-resolution”. It is related to both, statistical relationships between low-resolution and high-resolution. Several methods have been proposed to obtain better results, involving simple heuristics, edge modeling or statistical learning. The most powerful ones, …
Published in Journal of Web Engineering & Technology · Vol. 7, Issue 1, 2020 · pp. 21–29 Read article
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A Review of Computational Methods for Image Restoration and Noise Reduction Using Reference Images
Abstract: Digital imaging systems play a vital role in numerous application domains, including consumer photography, biomedical imaging, remote sensing, aerial surveillance, and astronomical observation. Despite continuous advancements in imaging hardware and software, the visual data acquired by these systems often suffer from degradation caused by spatially non-uniform blur. This blur may arise due to several factors, such as lens imperfections, atmospheric turbulence, sensor limitations, motion between the camera and the scene, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 23–30 Read article
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A Novel Approach to Edge Detection and Performance Measurebased on the Theory of “Range” and “Bowley’s Measure ofSkewness” in a Noisy Environment
Abstract: We proposed a new edge detection algorithm in a salt and pepper noisy environment without any pre-processing. The algorithm is a simple, unique mathematical expression. It is the product of three terms: median, range and some edge image enhancement constant. The algorithm assumes that the edge exists in an image at non-zero skewness. We also proposed a performance measure technique by using “Bowley's measure of Skewness”. The coefficient of Skewness …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 1, 2021 · pp. 31–38 Read article
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Contrast Image Enhancement Using Various Approaches: A Review
Abstract: AbstractImage enhancement is one of the most key issues in high quality pictures such as digital cameras and image research area. Since picture readability may be very effortlessly affected because of lighting fixtures during image acquiring, climate, or other equipment that has been used to seize the picture. These conditions may lead to image suffering from poor contrast and noise. Contrast enhancement converts the pixels depth of the input picture …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 39–45 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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A Review on Various Image and Video Restoration Techniques
Abstract: Reconstruction of low value deteriorated image into high quality improved image is termed as image restoration. The sight of this paper is to have knowledge about mixed restoration techniques like, average filter, median filter, wiener filter, blind de-convolution, and wavelet transform etc. The basis of restoration is to undo the operation of degraded image. There are many grounds because of which degradation takes place like, poor weather conditions, camera misfocus, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 50–58 Read article
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Analysis of Image Coders
Abstract: AbstractIn this paper we work on the performance analysis of well-known image compression algorithm i.e., wavelet based image compression which is Set Partition in Hierarchical Tree (SPIHT) and also no list SPIHT (NLS). As SPIHT uses three variable lists which require large hardware implementation and hence extra cost and high encoding and decoding time is required but NLS use marker instead of list which are placed on lower nodes of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 3, 2016 · pp. 26–30 Read article
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An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
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Detection and Diagnosis of Colorectal Cancer Using Image Processing
Abstract: Colorectal Cancer gets developed either in colon or in the rectum inside the large intestine, due to the abnormal growth of the cells. For detection and screening of colon cancer, Computed Tomography (CT) Colonography is a valid technique in which digital images of rectum polyps have been investigated. An improved gradient vector flow (IGVF) and various segmentation techniques of colorectal cancer detection are discussed in this paper. The segmented candidates …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 5, Issue 1, 2017 · pp. 11–14 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article