Image sensing is usually done with multiple sensors, like the RGB sensors in color imaging, the IR and EO sensors in surveillance and satellite imaging, etc. The resolution of each sensor can be increased by considering the images of the other sensors, and using the statistical redundancy among the sensors. Particularly, we use the fact that most discontinuities in the image of one sensor corre...

One can locate incoherent sources of light even when they are very close together within an error bound. This thesis contributes to knowledge by presenting progress towards experimentally realising the super-resolution of two incoherent point sources of light, using Fisher information gleaned through image-inversion interferometry measurements. The diffraction limit has been a limiting construc...

Super-resolution is the task of obtaining a high-resolution image of a scene given low resolution image(s) of the scene. Applications of super-resolution include forensic, satellite, medical imaging, surveillance, displaying video on large screens, etc [1]. Obtaining high-resolution images directly via better hardware (better image sensors, larger chip size) is quite costly. Furthermore, most o...

Light microscopy techniques have been vital to our understanding of biological structures and systems since their invention in the late 16 Century. However, conventional light microscopy techniques are limited by the diffraction limit of light, preventing us from seeing anything smaller than approximately 200 nm in x and y and approximately 500 nm in z. Many molecules and structures of interest...

This paper introduces a new examplar-based inpainting framework. A coarse version of the input image is first inpainted by a nonparametric patch sampling. Compared to existing approaches, some improvements have been done (e.g. filling order computation, combination of K nearest neighbours). The inpainted of a coarse version of the input image allows to reduce the computational complexity, to be...

Super-Resolution reconstruction produces one or a set of high-resolution images from a sequence of low-resolution frames. This article reviews a variety of Super-Resolution methods proposed in the last 20 years, and provides some insight into, and a summary of, our recent contributions to the general Super-Resolution problem. In the process, a detailed study of several very important aspects of...

Image enhancement of low-resolution images can be done throughmethods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resol...

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