In the imageprocessing domain, the growth of digital data has intensified the need for efficient and robust optimization techniques. This research study aims to develop and evaluate advanced optimization methods tail...
详细信息
ISBN:
(数字)9798350368413
ISBN:
(纸本)9798350368420
In the imageprocessing domain, the growth of digital data has intensified the need for efficient and robust optimization techniques. This research study aims to develop and evaluate advanced optimization methods tailored specifically for improving the performance of imageprocessing tasks. It explores the latest advancements in optimization algorithms, including evolutionary algorithms, metaheuristic approaches, and deep learning-based optimization techniques. The study provides an in-depth analysis of these methods, elucidating their strengths, weaknesses, and areas of applicability across diverse imageprocessing tasks such as image denoising, image reconstruction, image segmentation, and image enhancement. By comparing their performance through comprehensive experiments, the paper demonstrates substantial improvements in computational efficiency, accuracy, and generalization. These results highlight the potential of optimization methods to significantly enhance the quality and speed of imageprocessing pipelines, opening new avenues for breakthroughs in computer vision, medical imaging, remote sensing, and other domains. Ultimately, this research not only empowers practitioners with cutting-edge tools but also paves the way for future exploration in the application of optimization techniques within imageprocessing.
Audio Video coding Standard 3 (AVS3), which has been brought in many advanced algorithms and technologies on the basis of previous video coding standard, has already improved the coding efficiency greatly. However, wi...
详细信息
Infrared and visible image fusion is an important multimodal imageprocessing task that aims to enhance computer vision performance by effectively fusing infrared and visible images. Although in recent years, many dee...
Infrared and visible image fusion is an important multimodal imageprocessing task that aims to enhance computer vision performance by effectively fusing infrared and visible images. Although in recent years, many deep learning-based methods for infrared and visible image fusion have emerged. Howeve, most of these methods ignore the important role of semantic information in image fusion. Therefore, this paper proposes a semantic priori guided infrared and visible image fusion network called SPGFusion. It uses an adversarial generative network framework based on semantic priors to guide the infrared and visible image fusion process by combining a semantic feature-aware module and semantic generative adversarial loss. Experimental results demonstrate that the SPG-Fusion method yields more visually appealing fusion results and outperform state-of-the-art image fusion algorithms in visual quality and quantitative evaluation. The source code is available at https://***/tianzhiya/SPGFusion.
The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the ...
详细信息
ISBN:
(数字)9798350368888
ISBN:
(纸本)9798350368895
The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the high complexity of traditional imageprocessingalgorithms, existing VLP systems are unable to provide real-time positioning services. In response to the above issue, we propose an imageprocessing mechanism based on the inter-frame color feature matching method, which includes the equidistant sampling processing, low complexity decoding algorithm, and color feature matching-based LED region of interest (ROI) determination method. The results show that the system average positioning delay is 80.2ms, indicating better system real-time performance.
In this paper the authors presented a sophisticated data mining pipeline, which was designed for restoring the high-quality images from the blurred frames made by the Charge-Coupled Device (CCD) cameras. The developed...
详细信息
MWIR FPAs often contain a non-negligible number of dead pixels, and even clusters of pixels. In addition to the undesirable cosmetic effect that these flaws have on the output image, it can also be detrimental to down...
详细信息
ISBN:
(纸本)9781510650893;9781510650886
MWIR FPAs often contain a non-negligible number of dead pixels, and even clusters of pixels. In addition to the undesirable cosmetic effect that these flaws have on the output image, it can also be detrimental to downstream image exploitation efforts, including target detection and tracking algorithms. It is therefore necessary to mask such defects as early as possible, before it is exacerbated by the imaging pipeline processes, especially sharpening filters and contrast stretching, which are commonly used. This paper presents the results of an investigation into several dead-pixel replacement schemes of varying complexity, starting with simple replacement by the previous neighbor to interpolation using kernels of varying shapes and domain sizes. These are evaluated for accuracy, but also for their cluster-handling performance, latency impact, and suitability for real-time implementation on resource-constrained FPGA matrices. It is shown that asymmetric predictive kernels, optimized using neural nets or genetic algorithms, can offer significant improvements over naive last-good-neighbor replacement, while affording improved cluster-handling capability, low FPGA resource requirements, and incurring minimal and even zero latency.
The GPS is the most common used satellite-based navigation and positioning system. It is an indispensable component for a UAV as it provides accurate location data that is critical for navigation and mission success. ...
详细信息
By adopting an adaptive image quality evaluation method under adverse weather conditions, an advanced image defogging system has been developed. This system aims to predict the optimal algorithm for achieving the best...
详细信息
ISBN:
(数字)9798350373646
ISBN:
(纸本)9798350373653
By adopting an adaptive image quality evaluation method under adverse weather conditions, an advanced image defogging system has been developed. This system aims to predict the optimal algorithm for achieving the best image defogging results. The system integrates nine efficient defogging algorithms. To comprehensively evaluate the defogging performance of these algorithms, a set of evaluation metrics including PSNR, SSIM, LPIPS, ENL, MSE, and RMSE is employed to establish a comprehensive evaluation method. By calculating the values of these evaluation metrics, the optimal algorithm suitable for the image is predicted, and the defogged image produced by the optimal algorithm is processed to output the best-defogged image finally. All predicted data is stored in a database. When defogging an image, if there is matching data in the database, the corresponding optimal algorithm and imageprocessing are directly selected, thereby enhancing the overall defogging efficiency.
The imaging for small unmanned aerial vehicles (UAVs) in infrared imaging systems is easily disturbed when they shuttle between different surrounding regions in a large background, resulting in target contrast inversi...
详细信息
As computer technology and numerical algorithms rapidly develop, the role of computational fluid dynamics (CFD) in the fields of mechanical and aerospace engineering has become increasingly prominent. However, the out...
详细信息
暂无评论