To improve the spatial resolution of low resolution image with Gaussian blur and Pepper & salt noise, a blind single-image super resolution reconstruction method is proposed. In the low resolution imaging model, the Gaussian blur, down-sampling, as well as Pepper & Salt noise are all considered. Firstly, the Pepper & Salt noise in the low resolution image is reduced through median filtering met...

The process of Super Resolution (SR) aims at extracting a high resolution image from low resolution image. The proposed technique uses Redundant Wavelet Transform to enhance the resolution of an image using a single low resolution image. The proposed method decomposes the input image into different subbands. Then all subbands are interpolated. Combining all the interpolated subbands using Inver...

Despite significant progress, high-speed live-cell super-resolution studies remain limited to specialized optical setups, generally requiring intense phototoxic illumination. Here, we describe a new analytical approach, super-resolution radial fluctuations (SRRF), provided as a fast graphics processing unit-enabled ImageJ plugin. In the most challenging data sets for super-resolution, such as t...

The most sophisticated existing methods to generate 3D isotropic super-resolution (SR) from non-isotropic electron microscopy (EM) are based on learned dictionaries. Unfortunately, none of the existing methods generate practically satisfying results. For 2D natural images, recently developed super-resolution methods that use deep learning have been shown to significantly outperform the previous...

Abstract In this paper, we study the high-dimensional super-resolution imaging problem. Here, are given an image of a number point sources light whose locations and intensities unknown. The is pixelized blurred by known point-spread function arising from device. We encode unknown their via non-negative measure propose convex optimization program to find it. Assuming device’s componentwise decom...