A near-infrared (NIR) band provides information invisible to human eyes for discriminating and recognizing objects more clearly under low lighting conditions. To capture color and NIR images simultaneously, a multispectral filter array (MSFA) sensor is used. However, because lenses have different refractive indices for different wavelengths, lenses may fail to focus all rays to the same convergence. This is the reason an out-of-focus problem occurs and images are blurred. In this paper, a demosaicking algorithm that considers the out-of-focus problem is proposed. This algorithm is used by the MSFA of a red-green-blue-NIR image sensor to obtain color and NIR images. After the energies of the multispectral (MS) channels in the MSFA image are balanced to minimize aliasing, that image is filtered by the estimated low-pass kernel to generate a panchromatic (PAN) image. When an image is acquired, the out-of-focus problem and the formation process of the PAN image are modeled. The desired MS image is estimated by solving the least squares approach of the difference between the PAN and MS images based on the models. The experimental results show that the proposed algorithm performs well in estimating high-quality MS images and reduces the out-of-focus problem.
Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than
that of previous years. Image up-scaling algorithm is important issue since original input source is limited in transferring
within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is
able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to
estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.
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