RESTORATION OF COLOR IMAGES BY MULTICHANNEL KALMAN FILTERING

A multichannel image is a set of image planes that exhibit between-plane correlations. Degradation of multichannel imagery involves both within- and between-channel blurs. Restoration of such images using existing independent-channel filters is not appropriate because they fail both to restore the between-channel degradation and to incorporate between-channel correlations in the process. In this paper, a Kalman filter for optimal restoration of multichannel images is presented. This filter is derived using a multichannel semicausal image model that includes between-channel correlation and an imaging equation with between-channel degradation. Both stationary and nonstationary image models are developed. This filter is implemented in the Fourier domain and computation is reduced from O(LAMBDA-3N3M4) to O(LAMBDA-3N3M2) for an M x M N-channel image with degradation length LAMBDA. Color (red, green, and blue (RGB)) images are used as examples of multichannel images, and restoration in the RGB and YIQ domains are investigated. Simulations are presented in which the effectiveness of this filter is tested for different types of degradation and different image model estimates.