Microscopic analysis of images is more important for detail analysis of an image, Image super resolution (SR) reconstruction technique is increasing its attention from the image processing community, in the previous techniques, noise removal and smoothing techniques are used but image resolution improvement has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one or several low resolution (LR) images. This project is dealing with hybrid approach of combining SWT and DWT to improve the resolution of the image by interpolation. The...
High resolution (HR) images contain more image details, offer better visual perception and hence suc...
Resolution plays a major role for interpretation and analysis of an image. Super Resolution is a tec...
This project presents a self-similarity-based approach that is able to use large groups of similar p...
The suggested formula uses bilinear interpolation to enlarge the reduced resolution image by two occ...
High-resolution images are a fundamental requirement of modern imaging applications. However, sensor...
In many imaging applications, the acquisition of high resolution (HR) images/video is highly desirab...
In many imaging applications, the acquisition of high resolution (HR) images/video is highly desirab...
Since over three decades, computers have been widely used for processing and displaying images. The ...
Super-resolution image reconstruction provides an effective way to increase image resolution from a ...
Super-resolution (SR) is the process of obtaining a higher resolution image from a set of lower reso...
This problem addresses the problem of low-resolution image (noisy) that will proof later by PSNR num...
In the last three decades, multi-frame and single-frame super-resolution and reconstruction techniqu...
Image super resolution is to estimate a high resolution image from a low resolution image or a seque...
The main aim of super resolution image is to reconstruct a high-resolution(HR) image from low resolu...
This thesis investigates a number of techniques and algorithms for super resolution (SR) image recon...
High resolution (HR) images contain more image details, offer better visual perception and hence suc...
Resolution plays a major role for interpretation and analysis of an image. Super Resolution is a tec...
This project presents a self-similarity-based approach that is able to use large groups of similar p...
The suggested formula uses bilinear interpolation to enlarge the reduced resolution image by two occ...
High-resolution images are a fundamental requirement of modern imaging applications. However, sensor...
In many imaging applications, the acquisition of high resolution (HR) images/video is highly desirab...
In many imaging applications, the acquisition of high resolution (HR) images/video is highly desirab...
Since over three decades, computers have been widely used for processing and displaying images. The ...
Super-resolution image reconstruction provides an effective way to increase image resolution from a ...
Super-resolution (SR) is the process of obtaining a higher resolution image from a set of lower reso...
This problem addresses the problem of low-resolution image (noisy) that will proof later by PSNR num...
In the last three decades, multi-frame and single-frame super-resolution and reconstruction techniqu...
Image super resolution is to estimate a high resolution image from a low resolution image or a seque...
The main aim of super resolution image is to reconstruct a high-resolution(HR) image from low resolu...
This thesis investigates a number of techniques and algorithms for super resolution (SR) image recon...
High resolution (HR) images contain more image details, offer better visual perception and hence suc...
Resolution plays a major role for interpretation and analysis of an image. Super Resolution is a tec...
This project presents a self-similarity-based approach that is able to use large groups of similar p...