Efficient identification of arbitrary color filter array images based on the frequency domain approach

For reducing the cost, most digital cameras are equipped with a CCD or CMOS sensor and a RGB color filter array (CFA) for each pixel to capture one primary color component, and hence produce a mosaic image. Suppose the input mosaic image without the CFA structure information, this paper presents a novel efficient method, consisting of a training-based scheme and an identification scheme, for identifying its CFA structure using the frequency domain approach. Initially, based on a set of training mosaic images with different CFA structures, a training-based scheme is proposed to build up the representative spectrum for every CFA structure. As the model maps, the constructed representative spectra can be reused in subsequent identification processes. The proposed identification scheme first constructs the representative spectrum of the header-less input mosaic image as the query map. Then, a matching scheme is proposed to identify the corresponding CFA structure of the query map from the model maps. Experimental results demonstrate that the proposed identification method has low computational cost and high identification accuracy merits for mosaic images without prior header information, when compared with the state-of-the-art spatial domain-based method by Chiu et al.