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This paper discusses resolution enhancement of a set of images with varying exposure durations, having a high combined dynamic range. So far, little has been said in relation to the Human Visual System when it comes to Super-Resolution and High Dynamic Range fusion, unlike the case for traditional Super-Resolution where errors are measured with respect to human perception in the pixel domain. We propose...
Single-image super-resolution (SR) is to reconstruct a high-resolution image from a low-resolution input image. Nevertheless, most SR algorithms are performed in an iterative manner and are therefore time-consuming. In this paper, we propose an iteration-free single-image SR algorithm based on fast deconvolution with gradient prior. Based on the prior calculated from the initially upsampled image...
Super-resolution (SR) image reconstruction is a rapidly developing area in image processing. Especially, blind SR can generate high space resolution image without requiring priori information of the point spread function (PSF). In this paper, we propose a self-adaptive blind super-resolution image reconstruction approach which is based on multiple images. Our method can adaptively choose the parameter...
Regularization based super-resolution (SR) methods have been widely used to improve video resolution in recent years. These methods, however, only minimize the sum of difference between acquired low resolution (LR) images and observation model without considering video local structure. In this paper, we proposed an idea, which employs adaptive kernel regression on regularization based SR methods,...
Although super-resolution (SR) methods have been successfully used to improve the resolution of video content, these methods estimate high resolution (HR) frames without explicitly use local information. Instead, they minimize the sum of difference between acquired low resolution (LR) images and observation model. On the contrary, adaptive kernel regression estimates each pixel of HR frames independently...
The paper focuses on reconstructing the discontinuity between homogenous color regions in an interpolated image to improve its perceptual quality. A low-resolution input image is firstly interpolated and then decomposed into several patches. Each patch is then segmented into multiple homogenous regions using connected component analysis technique. Then a spatial-filter is applied to enhance the color/intensity...
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