Rzhanov Yuri
Center for Coastal and Ocean Mapping/Joint Hydrographic Center, University of New Hampshire, 24 Colovos Road, Durham, NH 03824, USA.
J Imaging. 2024 Jul 16;10(7):169. doi: 10.3390/jimaging10070169.
Knowledge of spectral sensitivity is important for high-precision comparison of images taken by different cameras and recognition of objects and interpretation of scenes for which color is an important cue. Direct estimation of quantum efficiency curves (QECs) is a complicated and tedious process requiring specialized equipment, and many camera manufacturers do not make spectral characteristics publicly available. This has led to the development of indirect techniques that are unreliable due to being highly sensitive to noise in the input data, and which often require the imposition of additional ad hoc conditions, some of which do not always hold. We demonstrate the reason for the lack of stability in the determination of QECs and propose an approach that guarantees the stability of QEC reconstruction, even in the presence of noise. A device for the realization of this approach is also proposed. The reported results were used as a basis for the granted US patent.
光谱灵敏度的知识对于高精度比较不同相机拍摄的图像以及识别物体和解释以颜色为重要线索的场景非常重要。直接估计量子效率曲线（QEC）是一个复杂且繁琐的过程，需要专门的设备，而且许多相机制造商并未公开其光谱特性。这导致了间接技术的发展，这些技术由于对输入数据中的噪声高度敏感而不可靠，并且通常需要施加额外的临时条件，其中一些条件并不总是成立。我们阐述了在确定QEC时缺乏稳定性的原因，并提出了一种即使在存在噪声的情况下也能保证QEC重建稳定性的方法。还提出了一种实现该方法的装置。所报告的结果被用作美国授权专利的依据。
