Yu K, Ji L, Wang L, Xue P
Opt Express. 2001 Jul 2;9(1):24-35. doi: 10.1364/oe.9.000024.
Quantization, which maps real values of raw data to a series of fixed gray levels, is an inevitable step in Optical Coherence Tomography (OCT) image formation. Three new quantization methods, Minimum Distortion, Information Expansion and Maximum Entropy are applied in the specific problem. Quantization results of a capillary with milk and the femoralis of rabbit are shown in this paper. Comparisons with the present log-based methods show that a suitable quantization method significantly increases contrast, SNR and visual fineness of the final image and reduces quantization error effectively. Applicability of different quantization methods is also discussed.
量化是光学相干断层扫描(OCT)图像形成过程中不可避免的一步,它将原始数据的实值映射到一系列固定的灰度级。本文将三种新的量化方法,即最小失真法、信息扩展法和最大熵法应用于特定问题。文中展示了牛奶填充毛细管和兔股动脉的量化结果。与现有的基于对数的方法相比,结果表明合适的量化方法能显著提高最终图像的对比度、信噪比和视觉清晰度,并有效降低量化误差。同时还讨论了不同量化方法的适用性。