Li Ting, Yao Binghui, Zhu Liquan, Deng Linxiao, Yang Yuhua, Chen Yuantong, Xu Lixin, Gu Chun
Opt Express. 2024 Jan 29;32(3):3891-3911. doi: 10.1364/OE.507868.
In pursuit of enhancing the display performance of gamut extension algorithms across diverse image types while minimizing image dependency, this study introduces a dynamic gamut extension algorithm. The algorithm is designed to extend the sRGB source gamut towards the wide gamut of a laser display. To evaluate its effectiveness, psychophysical experiments were conducted using four distinct image categories: complexions, scenery, objects, and color blocks and bars. The performance of the proposed algorithm was benchmarked against four established color gamut mapping algorithms. The comparative analysis revealed that our algorithm excels in handling wide color gamuts, outperforming the alternatives in terms of preference and the preservation of detail richness.
为了在尽量减少对图像依赖的同时，提高色域扩展算法在各种图像类型上的显示性能，本研究引入了一种动态色域扩展算法。该算法旨在将sRGB源色域扩展到激光显示器的宽色域。为了评估其有效性，使用四种不同的图像类别进行了心理物理实验：肤色、风景、物体以及色块和色条。将所提出算法的性能与四种既定的色域映射算法进行了基准测试。对比分析表明，我们的算法在处理宽色域方面表现出色，在偏好和细节丰富度保留方面优于其他算法。
