Super-Resolution for Synthetic Zooming

Super-Resolution for Synthetic Zooming

Optical zooming is an important feature of imaging systems. In this paper, we investigate a low-cost signal processing alternative to optical zooming—synthetic zooming by super-resolution (SR) techniques. Synthetic zooming is achieved by registering a sequence of low-resolution (LR) images acquired at varying focal lengths and reconstructing the SR image at a larger focal length or increased sp...

A Fuzzy Rule Based Approach for Image Zooming in Single Frame Super Resolution

To developing a novel fuzzy rule-based prediction framework used for high quality image zooming. This is developed using patch-based image zooming technique that is Low Resolution (LR) patch are replaced by estimated High Resolution (HR) patch. Using fuzzy rule algorithm the LR input image reconstructed into high quality images.

Multi-frame Super Resolution for Improving Vehicle Licence Plate Recognition

License plate recognition (LPR) by digital image processing, which is widely used in traffic monitor and control, is one of the most important goals in Intelligent Transportation System (ITS). In real ITS, the resolution of input images are not very high since technology challenges and cost of high resolution cameras. However, when the license plate image is taken at low resolution, the license...

Markov Networks for Super-resolution Markov Networks for Super-resolution

We address the super-resolution problem: how to estimate missing high spatial frequency components of a static image. From a training set of fulland lowresolution images, we build a database of patches of corrsponding highand low-frequency image information. Given a new low-resolution image to enhance, we select from the training data a set of 10 candidate high-frequency patches for each patch ...

Super-resolution fluorescent methods: where next for super-resolution?