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Previously we presented a selective image sharpening method with a coupled nonlinear diffusion process, and it sharpens only blurred edges without enhancing noise. Our prototypal color-image sharpening methods were formulated on the linear color models, namely, the channel-by-channel model and the 3D vector model. Our prototypal methods sharpen blurred color edges, but they do not necessarily enhance...
This paper presents a high-quality interpolation approach that can adjust edge sharpness and texture intensity to reconstruct an image according to user's taste in picture quality. Our interpolation approach first resolves an input image I into its skeleton image U and its texture generator V and its residual image D such that I = U·V + D, and then interpolates each of the three components independently...
Once image motion is accurately estimated, we can utilize those motion estimates for image sharpening and we can remove motion blurs. First, this paper presents a variational motion de-blurring method using a spatially variant model of motion blurs. The standard variational method is not proper for the motion de-blurring, because it is sensitive to model errors, and occurrence of errors are inevitable...
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