Moon Gi Kang

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In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for(More)
The determination of the regularization parameter is an important issue in regularized image restoration, since it controls the trade-off between fidelity to the data and smoothness of the solution. A number of approaches have been developed in determining this parameter. In this paper, a new paradigm is adopted, according to which the required prior(More)
This paper introduces an iterative regularized approach to increase the resolution of a video sequence. A multiple input smoothing convex functional is de ned and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly(More)
While high resolution images are required for various applications, aliased low-resolution images are only available due to the finite sensor pixels. In this paper; a new approach is proposed to obtain superresolution using regularization. With the proposed approach based on the discrete cosine transform, high-resolution images can be efficiently(More)
In this paper, we propose a chromatic aberration (CA) correction algorithm based on a false color filtering technique. In general, CA produces color distortions called color fringes near the contrasting edges of captured images, and these distortions cause false color artifacts. In the proposed method, a false color filtering technique is used to filter out(More)
In this paper, we formulate the colorization-based coding problem into an optimization problem, i.e., an <i>L</i><sub>1</sub> minimization problem. In colorization-based coding, the encoder chooses a few representative pixels (RP) for which the chrominance values and the positions are sent to the decoder, whereas in the decoder, the chrominance values for(More)
The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed observations is considered in this paper. The introduction of compression complicates the recovery problem. We analyze the DCT quantization noise and propose to model it in the spatial domain as a colored Gaussian process. This allows us to estimate the(More)