Dependent component analysis for multi-frame image restoration and enhancement

Independent component analysis (ICA) has been applied to the restoration of image sequences degraded by atmospheric turbulence. The original high-resolution image and turbulent sources were considered as independent sources from which the degraded image is composed of. Although the result was promising, the assumption of source independence may not be true in practice. In this paper, we propose to apply dependent component analysis (DCA), which can relax the independence assumption. The experimental result demonstrates DCA outperforms ICA under this circumstance, resulting in the flexibility in the use of adjacent image frames. In addition, the restored image can be further enhanced by employing a recently developed Gabor-filter-bank-based single-frame blind image deconvolution algorithm where DCA is also employed.