This paper presents a generalized Multiple-Kernel Fuzzy C-Means clustering (MKFCM) methodology for satellite image segmentation. Satellite images often require segmentation in the presence of uncertainty, caused due to factors like environmental conditions, poor resolution and poor illumination. Since any subsequent image analysis depends on the quality of such segmentation, one has to obtain an efficient algorithm for the purpose. Pixel clustering is a popular way of determining the homogeneous image regions, corresponding to the different land cover types, based on their spectral properties. The proposed MKFCM algorithm provides users a new flexible vehicle to fuse different pixel information in image-segmentation problems.