Over the last few years, image completion has made significant progress due to the generative adversarial networks (GANs) that are able to synthesize photorealistic contents. However, one of the main obstacles faced by many existing methods is that t...
Existing image completion methods are mostly based on missing regions that are small or located in the middle of the images. When regions to be completed are large or near the edge of the images, due to the lack of context information, the completion...
Image magnification can be reduced to construct an approximation surface with data points in the image while keeping image details and edge features. In this paper, a new image magnification method is proposed by constructing piecewise bicubic polyno...
To monitor the Earth’s surface, the satellite of the NASA Landsat program provides us image sequences of any region on the Earth constantly over time. These image sequences give us a unique resource to study the Earth’s surface, changes of the Earth...
Even though computer vision has been developing, edge detection is still one of the challenges in that field. It comes from the limitations of the complementary metal oxide semiconductor (CMOS) Image sensor used to collect the image data, and then im...
Pixel-level image manipulation localization requires separating weak forensic traces from image content while recovering manipulated regions under post-processing and domain shift. Existing methods do not jointly impose structured discrimination on m...
Image edge detection is a difficult task, because it requires the accurate removal of irrelevant pixels, while retaining important pixels that describe the image’s structural properties. Here, an artificial plant community algorithm is proposed...
Image classification is increasingly being utilized on construction sites to automate project monitoring, driven by advancements in reality-capture technologies and artificial intelligence (AI). Deploying real-time applications remains a challenge du...
Optical remote sensing images are easily affected by atmospheric absorption and scattering, and the low contrast and low signal-to-noise ratio (SNR) of aerial images as well as the different sensors of aerial and satellite images bring a great challe...
Damaged edges of bone tag images contain external factors such as impurities and damage, which affect the stitching process and lead to repair errors. Therefore, this paper proposes a stitching method based on image edge position feature matching. Th...
In order to improve the subjective and objective consistency of image sharpness evaluation while meeting the requirement of image content irrelevance, this paper proposes an improved sharpness evaluation method without a reference image. First, the p...
Multi-source image registration has often suffered from great radiation and geometric differences. Specifically, grayscale and texture from similar landforms in different source images often show significantly different visual features, and these dif...
Digital image watermarking aims to protect the information in an image without significantly affecting visual quality. In this paper, a new image watermarking technique has been proposed that uses Gaussian filters and first-order partial differential...
Semantic segmentation is an important field for automatic processing of remote sensing image data. Existing algorithms based on Convolution Neural Network (CNN) have made rapid progress, especially the Fully Convolution Network (FCN). However, proble...
Edge detection methods are significant in medical imaging-assisted diagnosis. However, existing methods based on grayscale gradient computation still need to be optimized in practicality, especially in terms of actual visual quality and sensitivity t...
Segmenting low-light images, such as images showing cracks on tunnel walls, is challenging due to limited visibility. Hence, we need to combine image brightness enhancement and a segmentation algorithm. We introduce essential preliminaries, specifica...
Significant progress has been made in single image super-resolution (SISR) based on deep convolutional neural networks (CNNs). The attention mechanism can capture important features well, and the feedback mechanism can realize the fine-tuning of the...
The detection of edges in images is a pressing issue in the field of image processing. This technique has found widespread application in image pattern recognition, machine vision, and a variety of other areas. The feasibility and effectiveness of gr...
The symmetrical difference kernel SAR image edge detection algorithm based on the Canny operator can usually achieve effective edge detection of a single view image. When detecting a multi-view SAR image edge, it has the disadvantage of a low detecti...
This paper presents an edge-based color image segmentation approach, derived from the method of particle motion in a vector image field, which could previously be applied only to monochrome images. Rather than using an edge vector field derived from...
The traditional SIFT (Scale Invariant Feature Transform) registration algorithm is highly regarded in the field of image processing due to its scale invariance, rotation invariance, and robustness to noise. However, it faces challenges such as a larg...
In this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To de...
In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated...
Images taken by digital cameras include noise. The image recognition rate decreases with increasing noise. Reducing noise is essential for improving the accuracy of image recognition. Low-pass filters, such as a Gaussian filter (GF), are often used t...
Steganography, a technique for concealing information, often faces challenges such as low decoding accuracy and inadequate extraction of edge and global features. To overcome these limitations, we propose a dual-stream U-Net framework with integrated...
Image interpolation plays an important role in many computer vision and image processing tasks, such as image resizing, denoising, and restoration. Most traditional interpolation algorithms work on the time domain and deal with all image regions in a...
In the era of widespread digital image sharing on social media platforms, deep-learning-based watermarking has shown great potential in copyright protection. To address the fundamental trade-off between the visual quality of the watermarked image and...
As a classic and effective edge detection operator, the Sobel operator has been widely used in image segmentation and other image processing technologies. This operator has obvious advantages in the speed of extracting the edge of images, but it also...
Remote sensing image super-resolution aims to reconstruct high-quality spatial details from low-resolution observations, which is essential for land-cover interpretation, object detection, and downstream geospatial analysis. However, existing convolu...
Effectively handling mixed noise types and varying intensities is crucial for accurate information extraction and analysis, particularly in resource-limited edge computing scenarios. Conventional image denoising approaches struggle with unseen noise...
With the rapid development of metasurface technology, metasurfaces have gained significant attention in optical edge detection. Owing to their precise control over the phase, amplitude, and polarization state of electromagnetic waves, metasurfaces of...
With the ability for all-day, all-weather acquisition, synthetic aperture radar (SAR) remote sensing is an important technique in modern Earth observation. However, the interpretation of SAR images is a highly challenging task, even for well-trained...
Pixelated images are used to transmit data between computing devices that have cameras and screens. Significant compression of pixelated images has been achieved by an “edge-based transformation and entropy coding” (ETEC) algorithm recent...
Advances in deep learning (DL) models and next-generation edge devices enable real-time image classification, driving a transition from the traditional, purely cloud-centric IoT approach to edge-based AIoT, with cloud resources reserved for long-term...
Image stitching aims to synthesize a wider and more informative whole image, which has been widely used in various fields. This study focuses on improving the accuracy of image mosaic and proposes an image mosaic method based on local edge contour ma...
During the harvesting and storage of wheat, various impurities are often mixed in, which adversely affect the processing quality and food safety of wheat. Therefore, developing an efficient and accurate impurity detection method is of great importanc...
As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with the aid of overlap functions, two new groups of fuzzy mathematical morphology (FMM) operators were proposed and applied to image...
Infrared imaging is based on thermal radiation and does not rely on visible light, allowing for it to operate normally at night and in low-light conditions. This characteristic is beneficial for regulatory authorities to monitor ships. Existing infra...
Synthetic aperture radar (SAR) image registration is an important process in many applications, such as image stitching and remote sensing surveillance. The registration accuracy is commonly affected by the presence of speckle noise in SAR images. Wh...
Infrared and visible image fusion (IVIF) fully integrates the complementary features of different modal images, and the fused image provides a more comprehensive and objective interpretation of the scene compared to each source image, thus attracting...
Image demosaicking has been an essential and challenging problem among the most crucial steps of image processing behind image sensors. Due to the rapid development of intelligent processors based on deep learning, several demosaicking methods based...
In this paper, we present a novel color edge detection method that integrates collaborative filtering with multiscale gradient fusion. The Block-Matching and 3D (BM3D) filter is utilized to enhance sparse representations in the transform domain, effe...
The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a rec...
Due to the wide availability of the tools used to produce manipulated images, a large number of digital images have been tampered with in various media, such as newspapers and social networks, which makes the detection of tampered images particularly...
To overcome the deficiencies in segmenting hot spots from thermal infrared images, such as difficulty extracting the edge features, low accuracy, and a high missed detection rate, an improved Mask R-CNN photovoltaic hot spot thermal image segmentatio...
Hyperspectral image (HSI) classification is a vital part of the HSI application field. Since HSIs contain rich spectral information, it is a major challenge to effectively extract deep representation features. In existing methods, although edge data...
Infrared and visible image fusion can integrate rich edge details and salient infrared targets, resulting in high-quality images suitable for advanced tasks. However, most available algorithms struggle to fully extract detailed features and overlook...
In recent years, the methods based on convolutional neural networks have achieved significant progress in hyperspectral image super-resolution. However, existing methods still face two key challenges: (1) they fail to fully extract edge detail inform...
Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use fundus photography to monitor the progression of certain eye conditions or diseases. Segmentation of the vessel tree is an essential process of retinal analysis....
With the rapid development of Internet of Things (IoT) technology, the number of devices connected to the network is exploding. How to improve the performance of edge devices has become an important challenge. Research on quality evaluation algorithm...
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