Learn More
Most commercial digital cameras use color filter arrays to sample red, green, and blue colors according to a specific pattern. At the location of each pixel only one color sample is taken, and the values of the other colors must be interpolated using neighboring samples. This color plane interpolation is known as demosaicing; it is one of the important(More)
Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video(More)
Resolution enhancement for video sequences has always been an attractive application in multimedia signal processing. " Superres-olution " methods, that combine non-redundant information from a set of low-resolution images, are beginning to be applied to the most popular video compression standard, MPEG. Bayesian approaches , which are very successful for(More)
Face images that are captured by surveillance cameras usually have a very low resolution, which significantly limits the performance of face recognition systems. In the past, super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. These techniques use super-resolution as a preprocessing step(More)
The bilateral filter is a nonlinear filter that does spatial averaging without smoothing edges; it has shown to be an effective image denoising technique. An important issue with the application of the bilateral filter is the selection of the filter parameters, which affect the results significantly. There are two main contributions of this paper. The first(More)
Most interest point detection algorithms are highly sensitive to illumination variations. This paper presents a method to find interest points robustly even under large non-uniform photometric changes. The method, which we call illumination robust feature extraction transform (IRFET), determines salient interest points in an image by calculating and(More)
—Super-resolution reconstruction is the process of reconstructing a high-resolution image from multiple low-resolution images. Most super-resolution reconstruction methods assume that exposure time is fixed for all observations, which is not necessarily true. In reality, cameras have limited dynamic range and nonlinear response to the quantity of light(More)
Superresolution (SR) is a well-known technique to increase the quality of an image using multiple overlapping pictures of a scene. SR requires accurate registration of the images, both geometrically and photometrically. Most of the SR articles in the literature have considered geometric registration only, assuming that images are captured under the same(More)