目的 针对已有的细节增强方法难以保持输入图像帧的色调分布的缺点，提出一种基于色调优化的图像视频细节增强算法。方法 首先，为了避免颜色通道的相关性所带来的偏色现象并提高算法效率，对输入图像帧进行颜色空间的转换，提取亮度信息。然后，采用基于局部极值的边缘保持图像滤波方法，快速地将亮度通道图像分解成一幅含有大尺度边缘信息的基图像和多幅含有小尺度细节信息的细节层图像。接着，在用户期望的细节增强系数和输入图像的颜色场的约束下，提出基于梯度域上能量优化的细节增强算法，获得色调一致的细节增强亮度图像。最后，通过颜色空间的逆转换得到最终的细节凸显效果。结果 实验结果表明，本文算法不但能够显著地增强输入图像帧的细节内容，而且能够有效地保持其原有的色调分布，显得更加真实生动。结论 本文算法基本满足科学观察、视频监控和数字视觉特效等领域的技术要求，具有很大的应用潜力。

Objective We propose a tone optimization-based image and video detail-enhancement algorithm to deal with the tone discrepancy between the input image and the detail-enhanced image in state-of-the-art methods.Method We first extract intensity information through color space conversion to improve efficiency and avoid the problem of color distortion that results from the correlation of color channels. Subsequently, we perform edge-preserving image filtering based on local extreme values to divide the intensity image rapidly into a base image containing coarse-scale information and several detail layer images containing fine-scale information. Under the constraints of user-specified detail-magnification coefficients and the color fields of the input image, a gradient domain energy optimization-based detail-enhancement algorithm is proposed to obtain the detail-exaggerated intensity image with tone consistency. Finally, we employ inverse color space conversion to obtain the detail-enhancement results.Result Results show that the proposed algorithm can achieve significant detail-enhancement effects with tone-preserving characteristics for arbitrary input images.Conclusion The proposed algorithm satisfies the technical requirements of image and video detail enhancement and shows great potential in various applications, such as scientific investigation, visual surveillance, and special visual effects.