Magnetic resonance (MR) images can be acquired by multiple receiver coil systems to improve signal-to-noise ratio (SNR) and to decrease acquisition time. The optimal SNR images can be reconstructed from the coil data when the coil sensitivities are known. In typical MR imaging studies, the information about coil sensitivity profiles is not available. In such cases the sum-of-squares (SoS) reconstruction algorithm is usually applied. The intensity of the SoS reconstructed image is modulated by a spatially variable function due to the non-uniformity of coil sensitivities. Additionally, the SoS images also have sub-optimal SNR and bias in image intensity. All these effects might introduce errors when quantitative analysis and/or tissue segmentation are performed on the SoS reconstructed images. In this paper, we present an iterative algorithm for coil sensitivity estimation and demonstrate its applicability for optimal SNR reconstruction and intensity inhomogeneity correction in phased array MR imaging.