The need of image registration is increasing, especially in the medical image domain. The simplest kind of image registration is to match two images that have similar intensity. More advanced cases include the problem of registering images of different intensity, for which phase based algorithms have proven to be superior. In some cases the phase based registration will fail as well, for instan...

To take a picture of scene, we acquire multiple images under different levels of flash intensity (possibly just " flash on " and " flash off "), and let the user subsequently adjust the flash level continuously by interpolating among the stored images. Camera motion is corrected using image registration techniques robust to intensity differences. Flash adjustment occurs either immediately on th...

Motion deblurring is a long standing problem in computer vision and image processing. In most previous approaches, the blurred image is modeled as the convolution of a latent intensity image with a blur kernel. However, for images captured by a real camera, the blur convolution should be applied to scene irradiance instead of image intensity and the blurred results need to be mapped back to ima...

This work presents a high-resolution image acquisition system by combining a multi-camera imaging system composed of multiple low-resolution digital cameras and a color super-resolution image reconstruction algorithm. Aligned and adjusted multiple mini-cameras and the controlling system consist the multi-camera imaging system. Some of the cameras obtain intensity information and the other ones ...

Intensity normalization is an important pre-processing step in the study and analysis of DaTSCAN SPECT imaging. As most automatic supervised image segmentation and classification methods base their assumptions regarding the intensity distributions on a standardized intensity range, intensity normalization takes on a very significant role. In this work, a comparison between different novel inten...