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. 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. Results show that the proposed algorithm can achieve significant detail-enhancement effects with tone-preserving characteristics for arbitrary input images. 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.