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31.
许静 《数字社区&智能家居》2009,(19)
文章介绍了图像增强的相关知识,重点介绍了用直方图增强图像的方法。用直方图处理图像包括直方图均衡化和直方图规定化。直方图均衡化和直方图规定化能增强图像的对比度,使图像更清晰。直方图均衡化对局部细节的增强效果不显著,而直方图规定化则使关注的细节变得更清晰。所以直方图规定化法处理医学图像局部细节方面优于均衡化。 相似文献
32.
研究并实现了指纹图像增强和纹线提取算法。改进了指纹脊线距离求取算法和基于脊线方向的纹线提取算法。实践表明,改进算法工作稳定,效果良好,鲁棒性强,对低质量图像具有显著的增强效果。 相似文献
33.
一种基于高频强调滤波和直方图均衡化的图像增强方法 总被引:2,自引:0,他引:2
直方图均衡化能够调节图像的动态灰度范围,是一种经典有效的图像增强方法,但它建立在合并相似像素灰度的基础之上,模糊了图像的细节。高频强调滤波将变换后的低频和高频分量都得到了增强,但是低频分量的增强要弱一些,这样会使得图像边缘更加清晰。实验表明,经该方法增强后的图像,其主观视觉效果明显改善。 相似文献
34.
针对软门限对信号噪声的滤除方法,在分析小波变换消噪原理和方法的基础上,具体分析了阈值对小波变换消噪的影响.提出了改进阈值的阈值函数,给出更好的滤波结果.实验表明这种改进的算法有效地提高了增强效果. 相似文献
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36.
实时图像增强算法改进及FPGA实现 总被引:2,自引:0,他引:2
针对复杂背景的多目标图像,提出了一种基于直方图的实时自适应图像增强方法.该方法根据自适应直方图窗口选择高低阈值,通过灰度线性变换及灰度级等间距密度均衡进行图像增强.利用该算法增强图像视频时,采用FPGA,通过并行处理结构及流水线技术,可实时处理每秒50帧780×582×12bits的可见光图像.在处理视频的过程中,由前一帧图像的直方图信息,来增强后一帧图像.理论分析和实验结果均表明,该算法克服了直方图均衡及平台直方图均衡增强图像引起的灰度断层现象,有效地增强了图像的对比度,提高了图像质量. 相似文献
37.
38.
《Displays》2023
Aiming at the poor adaptability and robustness of existing pseudo-color methods, most of which can only deal with an 8-bit grayscale, an adaptive enhancement algorithm of high grayscale images based on priori knowledge was proposed. Firstly, aiming at the problem that the original RGB color space is not easy to adjust dynamically, the power adjustment was integrated into the constructed high-bit chromatogram, and a power adaptive adjustment function based on the brightness priority over the original grayscale image was designed. Secondly, aiming at the problems of over-exposure, under-exposure, and poor gradients in RGB space, an adaptive grayscale correction algorithm was designed according to the priori knowledge distribution of RGB perceived brightness. Finally, to guarantee the color balance of the enhanced image, a color balance correction algorithm based on CMY space was designed. To verify the effectiveness of this method, it was applied to the pseudo-color enhancement of 16-bit pipeline CR images, 14-bit infrared images, 24-bit pipeline DR weld images, 8-bit or 24-bit rail crack images, and 16-bit remote sensing images respectively. The subjective and objective experimental results show that the design method has stronger adaptability, which has obvious advantages compared with the existing advanced high grayscale image enhancement methods. The enhancement effect is more coordinated, the processing result is more in line with human visual perception, and the details and texture information of the original image can be better preserved. 相似文献
39.
《Displays》2023
As a comprehensive integration of many new-generation information technologies, the metaverse has become a research hotspot that has attracted much attention. As a part of the metaverse, the industrial metaverse is expected to break through the constraints of space and time and promote high-quality industrial development. The industrial metaverse is human-centric, so its quality of experience (QoE) is a key topic. As one of the enabling technologies of the industrial metaverse, Mixed Reality (MR) can seamlessly integrate virtual information with the physical world and is widely regarded as an important window to the industrial metaverse. In close integration with other enabling technologies, industrial MR applications can be seen as a path toward the realization of the industrial metaverse; thus, the optimization of industrial MR applications can effectively achieve the QoE enhancement of the industrial metaverse. Based on the analysis of existing research and the characteristics of industrial scenarios, consistency, authenticity, smoothness, and comfort are identified as the factors that influence the user experience (UX) of industrial MR applications. Specific optimization methods for industrial MR applications are proposed to improve the UX with regard to these four factors. To verify the effectiveness of the proposed methods, a QoE evaluation model of the industrial metaverse based on the fuzzy analytic hierarchy process (FAHP) is established. Moreover, an industrial metaverse prototype for longwall mining that incorporates the proposed methods is developed and its QoE is evaluated. The results show that the proposed optimization methods for industrial MR applications significantly enhance the QoE in the industrial metaverse, and can provide better services for users in industrial systems, thus better serving these systems. 相似文献
40.
Most low-light image enhancement methods only adjust the brightness, contrast and noise reduction of low-light images, making it difficult to recover the lost information in darker areas of the image, and even cause color distortion and blurring. To solve the above problems, a global attention-based Retinex network (GARN) for low-light image enhancement is proposed in this paper. We propose a novel global attention module which computes multiple dimensional information in the channel attention module to help facilitate inference learning. Then the global attention module is embedded into different layers of the network to extract richer shallow texture features and deep semantic features. This means that the rich features are more conducive to learning the mapping relationship between low-light images to normal-light images, so that the detail recovery of dark regions is enhanced in low-light images. We also collected a low/normal light image dataset with multiple scenes, in which the images paired as training set can succeed to be applied to low-light image enhancement under different lighting conditions. Experimental results on publicly available datasets show that our method has better effectiveness and generality than the state-of-the-art methods in terms of evaluations metrics such as PSNR, SSIM, NIQE, Entropy. 相似文献