BBMS:通过基于深度图估计的双谐波小波提高浊度介质中单色图像可见度的研究

Q4 Computer Science
Sangita Roy
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引用次数: 0

摘要

电子成像需要高质量、高分辨率(HR)的数字图像来突出图像的细节。通常情况下,普通数码相机拍摄的图像会通过现有软件进行后期处理,而不是使用高成本的 CMOS 传感器相位相机。这些图像通常面临的问题是,散射介质会降低对比度,改变颜色,使整个图像发白。来自远处物体的信息会因介质传输不良和噪声放大而受到影响。双正交小波去噪(BWD)可在频率-时间空间中进行稀疏压缩,消除深度估计中的噪声,并使传输变得平滑。此外,单幅图像复原也是一个严峻的挑战和棘手的问题。恢复后的图像与退化图像相比有明显改善,消除了错误边缘检测的可能性,并防止了色彩偏移和低对比度。通过客观的评估,可以找到高质量的图像。此外,还对不同的小波、阈值和分解级别进行了研究和比较。由于采用了小波域分析,时间复杂度呈线性,这使得该技术快速、可靠、视觉效果好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BBMS: Investigation to Single Colour Image Visibility Improvement in Turbid Media through Biorthogonal Wavelet Based Depth-map Estimation
Electronic imaging needs good quality, high resolution (HR) digital images for highlighting finer details of the image. Normally images captured by ordinary digital camera are post pro cessed with available software instead of high cost CMOS sensor phased camera. Problem commonly faced with these images may get degraded due to the scattering media which deteriorates contrast, shifts colour, and make overall image whitish. Information from the distant objects suffer from poor medium transmission as well as noise amplification. Biorthogonal wavelet denoising (BWD), compress sparsely in frequency -time space, removes noise from depth estimation and makes the transmission smooth. Moreover, single image recovery is a serious challenge and ill posed problem. The recovered image improves compare to degraded image significantly and dis cards possibility of false edge detection as well as prevent colour shift and low contrast. Good quality images are found with objective evaluation. Moreover, different wavelets, thresholds, and decomposition levels have been studied and compared. Time complexity is linear due to wavelet domain analysis which makes the technique fast, reliable, and visually pleasing.
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来源期刊
Scientific Visualization
Scientific Visualization Computer Science-Computer Vision and Pattern Recognition
CiteScore
1.30
自引率
0.00%
发文量
20
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