To recover more valuable image details such as texture and brightness in low-contrast images, a new color image enhancement model is proposed based on the saturation-value total variation histogram equalization (SV-TV-HE) algorithm and combined with saturation-value total generalized variation (SV-TGV) and adaptive brightness function. A numerical algorithm is further designed for the proposed model using the alternating direction multipliers method to improve local brightness and contrast and maintain local details. Image enhancement experiments have been carried out for synthetic and real images. Experimental results show that the proposed model can effectively avoid the staircase effect in the process of image restoration, thereby achieving better image enhancement effect than existing methods in restoring image contrast, brightness, and other details.