In recent times, the use of multispectral images has rapidly grown in various fields like defense, agriculture, medicine, etc. However, the image acquisition technology for multispectral images is still in its primitive stages compared to the technology used in commercial digital color cameras. Digital color cameras use mosaicked technology for acquiring and forming color images. An array of sensors is used to capture one spectral band per pixel location. The final image is then formed by filling the missing spectral band intensity values at each pixel location. This process of estimating the full color image from the acquired sensor data is called demosaicking. In this paper, we propose to use the mosaicked technology for multispectral image acquisition systems. This paper focuses on developing demosaicking methods for such multispectral image acquisition systems. We explore ways of extending the existing demosaicking methods to multispectral images. This paper also addresses the problem of noise and degradations present during the acquisition process. The existing demosaicking methods tend to fail in the presence of external noise and degradations. To solve this problem, we have developed a maximum aposteriori probability (MAP) based method that performs demosaicking and at the same time reduces noise and degradations in the output. This novel approach treats the demosaicking problem as an image restoration problem and solves the optimization problem using the gradient descent method. The experimental results show that the MAP based demosaicking method provides a superior output compared to the traditional demosaicking methods. Various performance metrics have been used to compare results from different demosaicking algorithms.