[PDF] Top 20 Reverse Sparse Representation for Single Image Super-Resolution

... To further improve the quality of the output images, we employ several post-processing procedures. The non-local means (NLM) [37] regularization is based on the prior that the local image patches redundantly ... See full document

... an image represents the resolution of an ...the image and the width and height of the image represents the image ...an image occupies. Resolution of image applies ... See full document

... called super determination utilizing wavelet area introduction with edge extraction and scanty representation (SR-WDIEE-SR) has genuine points of interest, we have contrasted the proposed SR strategy and ... See full document

... high resolution image produce the low resolution ...low resolution of the original ...high resolution image, Has an Demirep and Gholamreza Anbarjafari [7] are Using the input ... See full document

... a super- resolved version of a LR textual image using sparse representation that suggest image patches from suitable dictionary ...clustered sparse coding approach for ... See full document

... spatial resolution is associated with a low spectral resolution and vice versa) with each ...spatial, resolution enhancement (RE) is ...vector-valued image regularization with partial ... See full document

... In the past several years, sparsity has been emerg- ing as one of the most significant properties of natural images [9]. The sparsity prior suggests that image patch can be well-represented as a sparse ... See full document

... hyperspectral image of the Indian Pines (200 spectral bands in the 400-2500 nm range, 145 × 145 pixels), obtained by the AVIRIS ...for super-resolution of this kind of ...panchromatic image ... See full document

... the image recovery stage, each patch at hand is recovered with each cluster dictionary by calculating the sparse representations and using the already designed HR dictionary and mapping ...the sparse ... See full document

... a single small 4″ × 4″ size color picture, scanned at 300 dots per inch (dpi) with 24 bits/pixel of true color, will produce a file containing more than 4 megabytes of ...large image files remain a major ... See full document

... other sparse coding approaches do not use the training samples for any purpose other than the dictionary construction, but in the proposed method they play a vital role as the neighborhood used for calculation of ... See full document

... 30. Do MN: Directional multiresolution image representations, M.S. thesis. Department of Communication, Swiss Federal Institute of Technology, Lausanne, Switzerland; November 2001. 31. Burt PJ, Adelson EH: The ... See full document

... a Super-Resolution method using learning MMPM technique for training and mixed matching for testing of ...feature representation of deep neural networks together to improve the performance of natural ... See full document

... higher image qual- ity as a means to sustain the information of the original ...a single or double precision floating point number from 8-bit image ...training image format is another concern, ... See full document

... years sparse representation has become a hot topic in the research of image representation model and there has been a growing interest in the study of image compression based on ... See full document

... an image super resolution method based on deep learning and sparse representation [15], which is used to deal with the details of vehicle images, so as to improve the recognition of ... See full document

... for single-image ...the image high-frequency details can be computed by the input low-frequency patches multiplied by a precomputed matrix, which is well trained by a large amount of low and high ... See full document

... The resolution of images is limited by the image acquisition devices, the optics, the hardware storage and other constraints in digital imaging ...subsequent image processing and analysis in most ... See full document

... for super-resolution is generally classified into 2 families of methods: (i) The classical multi-image super-resolution (combining pictures obtained at sub pixel misalignments), and ... See full document

... an image means a part of an image, which contains the specific size of pixel values of an ...original image will be cut into as many 33 × 33 patches to set as inputs in the convolutional neural ... See full document