Infrared Image Enhancement based on Saliency Weight with Adaptive Threshold

Fan, Fan; Ma, Yong; Huang, Jun; Liu, Zhe

doi:10.1109/siprocess.2018.8600468

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…Image brightness remains constant, converting the image to grayscale, subsequently facilitating the calculation of pixel velocity vectors. Second, region matching method [30]. Either through region or feature matching, this approach processes video sequences to locate, track, and derive useful displacements of moving targets.…”

Section: Optical Flow Methodsmentioning

confidence: 99%

Multi-Modal Fusion for Moving Object Detection in Static and Complex Backgrounds

Jiang,

2023

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Moving object detection from video sequences remains a focal point of research. To address the limitations evident in current methodologies, a synthesis of optical flow method and salient object fusion algorithm has been applied. Utilising the Graph-based Visual Saliency (GBVS) algorithm, significant target region signals from both static and dynamic images can be obtained. This technique captures valuable image target information, highlighting conspicuous targets within dynamic visuals. Concurrently, target signals can be isolated employing the Harmony Search (HS) algorithm, enhancing the accuracy in identifying moving objects. A weighted fusion of the extracted salient regions by the GBVS algorithm and the moving objects identified by the HS algorithm was executed in this study. This amalgamation demonstrates efficacy in extracting static objects in rudimentary environments and complex backgrounds alike. MATLAB simulation experiments have indicated that such a multi-modal fusion not only diminishes background noise but also proficiently isolates the entirety of the target. Building on traditional frame difference and background difference methods and considering the properties of the field programmable gate array (FPGA) alongside off-chip synchronous dynamic memory's access control prerequisites, adaptations for these algorithms were conceived using FPGA logic units.

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Section: Optical Flow Methodsmentioning

confidence: 99%

Multi-Modal Fusion for Moving Object Detection in Static and Complex Backgrounds

Jiang,

2023

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“…In addition, infrared images can prevent interference from dust or markers and avoid false alarms during the detection process. Infrared images have been widely used in the field of detection, but due to the imaging principle of infrared images, infrared images usually have problems such as low contrast, high noise, and fuzzy edges, and the images often also have uneven intensity during the acquisition process [2][3][4][5][6]. The inhomogeneity of image intensity can have a great impact on image segmentation, and Kass et al proposed a widely used model for inhomogeneous density images, active contour model (ACM) [7].…”

Section: Introductionmentioning

confidence: 99%

The Segmentation of Wind Turbine Defect Based on UAV Infrared Image

Wang,

Jiang,

Wen

et al. 2023

Proccedings of the 2023 International Conference on Quantitative InfraRed Thermography

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During the operation of wind power systems, problems such as damage may occur, in order to keep the system running normally and safely, regular maintenance of wind turbines is essential. Currently, the main treatment is to detect the blades by carrying an infrared camera on board a UAV. However, infrared images can suffer from significant inhomogeneities due to the inconsistent response of the detector array of the infrared camera, the inconsistent spectral response of the infrared detector to environmental variations and incoming background radiation, and the combined effect of the camera's optical lens. The inhomogeneity of an image can greatly affect the accuracy of image segmentation. To solve this problem, In this paper, we propose a method for rapidly segmenting inhomogeneous images. Specifically, we introduce global and local information of the image into the energy term. We also introduce a detail map as the reference map for the edge stopping function, which improves the robustness of the image to the initial contour and improves the segmentation accuracy of inhomogeneous images while speeding up the segmentation. Correction of bias field is also realized simultaneously. The results demonstrate that our method achieves average accuracy of 96% in the task of performing segmentation of wind turbine defects with the shortest running time. Notably, our segmentation efficiency surpasses that of mainstream level-set techniques.

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“…In the field of image processing, salient object detection [1,2] or visual saliency prediction [3][4][5][6] has been conducted for implementing the human visual attention mechanism on computers. Specifically, the maps representing salient regions in images are called a Universal Saliency Map (USM), and their applications are abundant such as image re-targeting [7,8], image enhancement [9,10], and image compression [11,12]. For the purpose of modeling human instinctive perception, the USM, which is common to humans, is calculated as highlighting regions more attentive than their surroundings [5].…”

Section: Introductionmentioning

confidence: 99%

Few-Shot Personalized Saliency Prediction with Similarity of Gaze Tendency Using Object-Based Structural Information

Moroto

Maeda

Ogawa

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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This paper presents a few-shot personalized saliency prediction method with similarity of gaze tendency using object-based structural information. The personalized saliency maps (PSMs) that represent the individual visual attention can be used for analyzing the heterogeneity among personalized preferences, whereas general saliency maps ignore the individual differences. However, the PSM prediction is a difficult task since the acquisition of eye tracking data, which are needed for obtaining PSMs, gives persons a heavy burden. Then, for realizing PSM prediction with a limited amount of training data, the use of the similarity of gaze tendency between persons can be one effective way. It has been reported that human gazes are related to objects and their relative relationships that are semantic and structural information, and we focus on the integration of PSMs predicted for other persons by using object-based similarities of gaze tendency. The advantage in this paper is that we newly focus on similarities of gaze tendency for visually similar objects for solving the lack of eye tracking data by considering both semantic and structural information, simultaneously. By experimenting with the open dataset, the proposed method outperforms the state-of-the-art methods.

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Infrared Image Enhancement based on Saliency Weight with Adaptive Threshold

Cited by 5 publications

References 19 publications

Multi-Modal Fusion for Moving Object Detection in Static and Complex Backgrounds

Multi-Modal Fusion for Moving Object Detection in Static and Complex Backgrounds

The Segmentation of Wind Turbine Defect Based on UAV Infrared Image

Few-Shot Personalized Saliency Prediction with Similarity of Gaze Tendency Using Object-Based Structural Information

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