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This paper presents a novel image restoration algorithm using examples and truncated constrained least squares (TCLS) filter for ultra-high definition (UHD) television systems. The proposed approach consists of three steps: (i) generation of the patch dictionary using multiple-step image blurring, (ii) selection of the optimum patch based on the orientation and the amount of blurring, and (iii) combination...
This paper presents a novel super-resolution (SR) algorithm using local self-examples. The proposed algorithm consists of three steps: i) generation of the patch dictionary using multiple-step image blurring, ii) search of the optimum patches using the magnitude and orientation of the image gradient, and iii) combination of the restored and original patches for reducing the patch-mismatching error...
A finite impulse response (FIR) filter design method is presented by truncating the constrained least squares filter for real-time, spatially adaptive image restoration. The proposed method truncates the original constrained least squares image restoration filter using the Maxwell-Boltzmann distribution kernel. For the edge preserving image restoration, the orientation of local edge is analyzed based...
In this paper, a novel single image super-resolution (SR) method is presented using variable sampling positions. The proposed method estimates a sampling position correction vector (SPCV) from the regularly sampled data based on the local gradient of the image. In pursuit of both preserving edge and removing unnatural artifacts in the SR process, non-uniformly sampled data obtained by the SPCV is...
This paper presents a novel real-time super-resolution (SR) method using directionally adaptive image interpolation and image restoration. The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation...
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