A novel texture based color image enhancement methodology that focuses on an automated way of target image generation is proposed here. The images in the database with highest histogram correlation with input image are identified for extracting different features. Target image is obtained by fusing images selected based on minimum Euclidean distance between extracted features. The proposed method is a simple color image enhancement methodology where the range (the gamut) of the R, G, and B channels is optimally preserved. We derive a new quantitative validation approach to identify visibility loss problem that may occur during enhancement. The maximum possible contrast enhancement is achieved by stretching the intervals of the color levels to the maximum possible extent using a sigmoid function. The proposed method has been compared with other state-of-the-art algorithms reported in the literature. © 2015 The Authors.