- 标题
- 摘要
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- 实验方案
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Spatiotemporal Adaptive Nonuniformity Correction Based on BTV Regularization
摘要： The residual nonuniformity response, ghosting artifacts, and over-smooth effects are the main defects of the existing nonuniformity correction (NUC) methods. In this paper, a spatiotemporal feature-based adaptive NUC algorithm with bilateral total variation (BTV) regularization is presented. The primary contributions of the innovative method are embodied in the following aspects: BTV regularizer is introduced to eliminate the nonuniformity response and suppress the ghosting effects. The spatiotemporal adaptive learning rate is presented to further accelerate convergence, remove ghosting artifacts, and avoid over-smooth. Moreover, the random projection-based bilateral filter is proposed to estimate the desired target image more accurately which yields more details in the actual scene. The experimental results validated that the proposed algorithm achieves outstanding performance upon both simulated data and real-world sequence.
关键词： infrared image sensors,Infrared imaging,neural networks,image denoising
更新于2025-09-23 15:23:52
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Ship detection in spaceborne infrared images based on Convolutional Neural Networks and synthetic targets
摘要： Automatic detection of ships in spaceborne infrared images is important for both military and civil applications due to its all-weather detection capability. While deep learning methods have made great success in many image processing fields recently, training deep learning models still relies on large amount of labeled data, which may limit its application performance for infrared images target detection tasks. Considering that, we propose a new infrared ship detection method based on Convolutional Neural Networks (CNN) which is trained only with synthetic targets. For the problem of limited infrared training data, we design a Transfer Network (T-Net) to generate large amount of synthetic infrared-style ship targets from Google Earth images. The experiments are conducted on a near infrared band image (0:845μm s 0:885μm), a short wavelength infrared band image (1:560μm s 1:66μm) and a long wavelength infrared band image (2:1μm s 2:3μm) of Landsat-8 satellite. The results demonstrate the effectiveness of the target generation ability of T-Net. With only synthetic training samples, our detection method achieves a higher accuracy than other classical ship detection methods.
关键词： Convolutional Neural Networks,Spaceborne infrared image,Synthetic targets,Ship detection
更新于2025-09-23 15:23:52
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Infrared Image Reconstruction Based on Archimedes Spiral Measurement Matrix
摘要： It is a new research direction to realize infrared (IR) image reconstruction using compressed sensing (CS) theory. In the field of CS, the construction of measurement matrix is very principal. At present, the types of measurement matrices are mainly random and deterministic. The random measurement matrix can well satisfy the property of measurement matrix, but needs a large amount of storage space and has an inconvenient in hardware implementation. Therefore, a deterministic measurement matrix construction method is proposed for IR image reconstruction in this paper. Firstly, a series of points are collected on Archimedes spiral to construct a definite sequence; then the initial measurement matrix is constructed; finally, the deterministic measurement matrix is obtained according to the required sampling rate. Simulation results show that the IR image could be reconstructed by the measured values obtained through the proposed measurement matrix. Moreover, the proposed measurement matrix has better reconstruction performance compared with the Gaussian and Bernoulli random measurement matrices.
关键词： deterministic measurement matrices,compressed sensing (CS),infrared image reconstruction
更新于2025-09-23 15:23:52
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Steam piping infrared image segmentation with trend coefficients algorithm
摘要： In the industrial production or life of mankind, the use of steam piping network brings convenience and rapidity. As we all know, steam piping are often applied to transport high-temperature materials. Excessive temperature often has potential safety hazards or causes waste of resources. This requires real-time monitoring of abnormal phenomena such as excessive local temperature in steam pipelines. Based on the characteristics of infrared images, steam network pipe images can be easily captured by infrared thermal imager. However, the complexity and diversity of the environment make it difficult for infrared images to directly distinguish the high temperature area and normal temperature area of the pipes. In order to solve this problem, this paper proposes a trend coefficient algorithm for infrared spectroscopy image. Firstly, one-dimensional single-threshold Otsu method is extended to one-dimensional multi-threshold acquisition, and then one-dimensional method is extended to two-dimensional method to form two-dimensional double-threshold Otsu segmentation algorithm. The algorithm includes the trace of between-class scatter matrix as the evaluation function, and analyzes the trend coefficient to obtain the optimal threshold. Through the simulation experiment of MATLAB, it can be seen that the method can clearly get the distribution of high temperature area of pipeline image. It not only extracts the pipeline area from the image, but also accurately segments and locates the over-temperature area on the steam pipeline image. And it also eliminates the interference of trees and shrubs in the outdoor environment to a certain extent. Under the characteristics of different steam pipeline images, the evaluation results confirm that the proposed method can locate and segment the high temperature area of pipeline accurately.
关键词： Infrared high temperature region,Steam piping infrared image segmentation,Trend coefficients algorithm
更新于2025-09-23 15:22:29
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An improved infrared image processing method based on adaptive threshold denoising
摘要： This paper combines the image adaptive threshold denoising algorithm and performs double threshold mapping processing to the infrared image, which effectively reduces the influence of these phenomena to the infrared image and improves the quality of the image. In this paper, the infrared image denoising technology is studied, and an infrared image denoising method based on the wavelet coefficient threshold processing is proposed. This method is based on the noise distribution characteristics of infrared images, the multiplicative noise in the infrared image is transformed into an additive noise, and the wavelet transform coefficient of the transformed infrared image is processed to denoise the image. On this basis, the advantages and disadvantages of the soft and hard threshold functions are deeply analyzed, and an adaptive threshold function with adjustable parameter is constructed. At the same time, in order to suppress the Gibbs visual distortion caused by the absence of translation invariance of the orthogonal wavelet transform, the two-input wavelet transform with translation invariance is introduced, and a double threshold mapping infrared image processing method based on the adaptive threshold denoising algorithm based on the two-input wavelet transform is formed. Simulation results show that the method proposed in this paper has a better suppression of noise, maintains the integrity of image details, and improves the image quality to a certain extent.
关键词： Threshold function,Double threshold mapping,Image denoising,Binary wavelet transform,Infrared image
更新于2025-09-23 15:22:29
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Infrared Small Target Detection via Non-Convex Rank Approximation Minimization Joint l2,1 Norm
摘要： To improve the detection ability of infrared small targets in complex backgrounds, a novel method based on non-convex rank approximation minimization joint l2,1 norm (NRAM) was proposed. Due to the defects of the nuclear norm and l1 norm, the state-of-the-art infrared image-patch (IPI) model usually leaves background residuals in the target image. To fix this problem, a non-convex, tighter rank surrogate and weighted l1 norm are instead utilized, which can suppress the background better while preserving the target efficiently. Considering that many state-of-the-art methods are still unable to fully suppress sparse strong edges, the structured l2,1 norm was introduced to wipe out the strong residuals. Furthermore, with the help of exploiting the structured norm and tighter rank surrogate, the proposed model was more robust when facing various complex or blurry scenes. To solve this non-convex model, an efficient optimization algorithm based on alternating direction method of multipliers (ADMM) plus difference of convex (DC) programming was designed. Extensive experimental results illustrate that the proposed method not only shows superiority in background suppression and target enhancement, but also reduces the computational complexity compared with other baselines.
关键词： infrared image,structured norm,non-convex rank approximation minimization,small target detection
更新于2025-09-23 15:22:29
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Infrared-based Autonomous Navigation for Civil Aircraft Precision Approach and Landing
摘要： Precise navigation is a fundamental problem of aircraft safety approach and landing. However, existing methods including rotorcraft-based and fixed-wing-based cannot meet the requirements of precision approach and landing of civil aircraft in Global Position System (GPS)-denied and low visibility. This paper proposes an autonomous approach and landing navigation method whose accuracy is comparable to Inertial/ Differential GPS (DGPS) integration. This method integrates inertial data, forward looking infrared (FLIR) images and runway geographic information to estimate kinetics states of aircraft during approach and landing. Firstly, we improve an existing method to robustly detect runway, accurately extract three vertexes of runway contour from FLIR images, and synthetize virtual runway features by runway geo-information and aircraft’s pose parameters. Secondly, we propose to use real and synthetic runway features to create vision cues and integrate them with inertial data in Square-root Unscented Kalman Filter (SR-UKF) to estimate motion errors. Meanwhile, the measured motion states are corrected with the estimated state errors. Finally, we design a flight data acquisition platform equipped on a general aircraft, and use the real flight data to verify our proposed method. The experimental results demonstrate that the proposed method can run smoothly for civil aircraft precision approach and landing.
关键词： approach and landing,runway detection,Civil aircraft,infrared image,autonomous navigation
更新于2025-09-23 15:22:29
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A novel method on the edge detection of infrared image
摘要： Infrared image processing is important for fault identification of high-voltage equipment. This paper studies the problem on the edge detection of infrared image. First a kind of spiking neural network is constructed, and by using the characteristics of the spiking neuron, a novel method is designed to achieve the edge detection of infrared image. Finally, some typical examples are included and corresponding experimental results show the effectiveness and advantage of the proposed method.
关键词： spiking neural network,Edge detection,infrared image
更新于2025-09-23 15:21:21
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[IEEE NAECON 2019 - IEEE National Aerospace and Electronics Conference - Dayton, OH, USA (2019.7.15-2019.7.19)] 2019 IEEE National Aerospace and Electronics Conference (NAECON) - In Situ Process Monitoring for Laser-Powder Bed Fusion using Convolutional Neural Networks and Infrared Tomography
摘要： Additive Manufacturing (AM) is a growing field for various industries of avionics, biomedical, automotive and manufacturing. The onset of Laser Powder Bed Fusion (LPBF) technologies for metal printing has shown exceptional growth in the past 15 years. Quality of parts for LPBF is a concern for the industry, as many parts produced are high risk, such as biomedical implants. To address these needs, a LPBF machine was designed with in-situ sensors to monitor the build process. Image processing and machine learning algorithms provide an efficient means to take bulk data and assess part quality, validating specific internal geometries and build defects. This research will analyze infrared (IR) images from a Selective Laser Melting (SLM) machine using a Computer Aided Design (CAD) designed part, featuring specific geometries (squares, circles, and triangles) of varying sizes (0.75-3.5 mm) on multiple layers for feature detection. Applying image processing to denoise, then Principal Component Analysis (PCA) for further denoising and applying Convolution Neural Networks (CNN) to identify the features and identifying a class which does not belong to a dataset, where a dataset are created from CAD images. Through this automated process, 300 geometric elements detected, classified, and validated against the build file through CNN. In addition, several build anomalies were detected and saved for end-user inspection.
关键词： Laser Powder Bed Fusion (LPBF),Principal Component Analysis (PCA),infrared image (IR),Convolution Neural Networks (CNN),Additive Manufacturing (AM),Computer Aided Design (CAD)
更新于2025-09-23 15:21:01
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[Lecture Notes in Computer Science] Pattern Recognition and Computer Vision Volume 11259 (First Chinese Conference, PRCV 2018, Guangzhou, China, November 23-26, 2018, Proceedings, Part IV) || Infrared Small Target Detection Using Multiscale Gray and Variance Difference
摘要： Infrared small target detection plays an important role in infrared monitoring and early warning systems. This paper proposes a local adaptive contrast measure for robust infrared small target detection using gray and variance di?erence. First, a size-adaptive gray-level target enhancement process is performed. Then, an improved multiscale variance di?erence method is proposed for target enhancement and cloud clutter removal. To demonstrate the e?ectiveness of the proposed approach, a test dataset consisting of two infrared image sequences with di?erent backgrounds was collected. Experiments on the test dataset demonstrate that the proposed infrared small target detection method can achieve better detection performance than the state-of-the-art approaches.
关键词： Small target detection,Infrared image,Local di?erence measures
更新于2025-09-23 15:21:01