在长期的计算机视觉技术发展过程中,研究者们主要处理的对象是通过图像信号处理器(Image Signal Processor,ISP)处理后的标准RGB图像。这类图像体积小,方便使用和网络传播,因而在许多传统应用场景中得到广泛应用。然而,在低光照或极端...在长期的计算机视觉技术发展过程中,研究者们主要处理的对象是通过图像信号处理器(Image Signal Processor,ISP)处理后的标准RGB图像。这类图像体积小,方便使用和网络传播,因而在许多传统应用场景中得到广泛应用。然而,在低光照或极端成像条件下,这类经过压缩和处理的图像往往因模糊、量化等不可逆操作,导致细节丢失,限制了其性能表现。为应对这些挑战,越来越多的研究开始关注直接处理相机传感器输出的RAW图像。RAW图像未经过复杂的ISP处理,具有线性响应、高比特深度和无损压缩的特点,能够保留更多的原始感光信息。这些特性使其在低光、高动态范围以及复杂视觉场景中表现出优异的灵活性和潜力。在近年来的研究中,RAW图像处理技术取得了显著进展,其应用已从高质量图像与视频的获取、去噪与增强,扩展到目标识别、场景理解等计算机视觉任务。相比传统RGB图像,RAW图像处理能够更好地保留细节信息,并在特定条件下显著提升视觉任务的精度和鲁棒性。此外,随着深度学习技术的发展,基于RAW数据的端到端模型设计成为了新的研究方向,能够充分利用图像中的原始信号信息来提升视觉处理效果。本文系统性地综述了RAW图像处理技术的最新进展,并探讨了这些技术在计算机视觉各领域中的应用。同时,本文还展望了未来的发展趋势,特别是RAW图像数据在更复杂场景下的应用潜力,为相关研究者和从业者提供了有价值的参考和启示。展开更多
Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, fo...Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, for example, sway yaw and surge that are the most important error sources. The phase error of a wide band synthetic aperture sonar is modeled and solutions to sway yaw and surge motion estimation based on the raw sonar echo data with a Displaced Phase Center Antenna (DPCA) method are proposed and their implementations are detailed in this paper. It is shown that the sway estimates can be obtained from the correlation lag and phase difference between the returns at coincident phase centers. An estimate of yaw is also possible if such a technique is applied to more than one overlapping phase center positions. Surge estimates can be obtained by identifying pairs of phase centers with a maximum correlation coefficient. The method works only if the platform velocity is low enough such that a number of phase centers from adjacent pings overlap.展开更多
文摘在长期的计算机视觉技术发展过程中,研究者们主要处理的对象是通过图像信号处理器(Image Signal Processor,ISP)处理后的标准RGB图像。这类图像体积小,方便使用和网络传播,因而在许多传统应用场景中得到广泛应用。然而,在低光照或极端成像条件下,这类经过压缩和处理的图像往往因模糊、量化等不可逆操作,导致细节丢失,限制了其性能表现。为应对这些挑战,越来越多的研究开始关注直接处理相机传感器输出的RAW图像。RAW图像未经过复杂的ISP处理,具有线性响应、高比特深度和无损压缩的特点,能够保留更多的原始感光信息。这些特性使其在低光、高动态范围以及复杂视觉场景中表现出优异的灵活性和潜力。在近年来的研究中,RAW图像处理技术取得了显著进展,其应用已从高质量图像与视频的获取、去噪与增强,扩展到目标识别、场景理解等计算机视觉任务。相比传统RGB图像,RAW图像处理能够更好地保留细节信息,并在特定条件下显著提升视觉任务的精度和鲁棒性。此外,随着深度学习技术的发展,基于RAW数据的端到端模型设计成为了新的研究方向,能够充分利用图像中的原始信号信息来提升视觉处理效果。本文系统性地综述了RAW图像处理技术的最新进展,并探讨了这些技术在计算机视觉各领域中的应用。同时,本文还展望了未来的发展趋势,特别是RAW图像数据在更复杂场景下的应用潜力,为相关研究者和从业者提供了有价值的参考和启示。
文摘Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, for example, sway yaw and surge that are the most important error sources. The phase error of a wide band synthetic aperture sonar is modeled and solutions to sway yaw and surge motion estimation based on the raw sonar echo data with a Displaced Phase Center Antenna (DPCA) method are proposed and their implementations are detailed in this paper. It is shown that the sway estimates can be obtained from the correlation lag and phase difference between the returns at coincident phase centers. An estimate of yaw is also possible if such a technique is applied to more than one overlapping phase center positions. Surge estimates can be obtained by identifying pairs of phase centers with a maximum correlation coefficient. The method works only if the platform velocity is low enough such that a number of phase centers from adjacent pings overlap.
