Remote sensing applications such as clustering, classification, feature extraction, measurement and change detection need fused high-resolution images that contain complementary information coming from multispectral bands. To transfer as much information as possible from source images to the fused image, image fusion can be considered as an optimization problem. In this paper, a new, two-stage, multi-spectral, region based, optimal fusion method is proposed. Panchromatic and infrared bands of Landsat 8 satellite images are fused with K-medoids segmentation and Differential Search Algorithm (DSA). The fused image is combined with the red, green, and blue (RGB) bands of the same area with intensity-hue-saturation (IHS) transform. Experiments carried out on test images indicate that developed method performed better than most of the state-of-theart fusion techniques in terms of both visual and numerical evaluations.