Learn More
This paper proposes a robust single-image super-resolution method for enlarging low quality web image/video degraded by downsampling and compression. To simultaneously improve the resolution and perceptual quality of such web image/video, we bring forward a practical solution which combines adaptive regularization and learning-based super-resolution. The(More)
Coded aperture snapshot spectral imaging (CASSI) provides an efficient mechanism for recovering 3D spectral data from a single 2D measurement. However, since the reconstruction problem is severely underdetermined, the quality of recovered spectral data is usually limited. In this paper we propose a novel dual-camera design to improve the performance of(More)
Example-based super-resolution recovers missing high frequencies in a magnified image by learning the correspondence between co-occurrence examples at two different resolution levels. As high-resolution examples usually contain more details and are of higher dimensionality in comparison with low-resolution ones, the mapping from low-resolution to(More)
This correspondence presents an image compression approach that integrates our proposed parameter-assistant inpainting (PAI) to exploit visual redundancy in color images. In this scheme, we study different distributions of image regions and represent them with a model class. Based on that, an input image at the encoder side is divided into featured and(More)
This paper carves out an image compression approach that integrates our parameter-assistant inpainting (PAI) technique to exploit the visual redundancy inherent in color-gradation image regions. In our scheme, an input image is first classified at block level according to the degree of edge content as well as chromatic variation in each block. An exemplar(More)
Time multiplexing (TM) and spatial neighborhood (SN) are two mainstream structured light techniques widely used for depth sensing. The former is well known for its high accuracy and the latter for its low delay. In this paper, we explore a new paradigm of scalable depth sensing to integrate the advantages of both the TM and SN methods. Our contribution is(More)
This paper proposes novel density modulated binary patterns for depth acquisition. Similar to Kinect, the illumination patterns do not need a projector for generation and can be emitted by infrared lasers and diffraction gratings. Our key idea is to use the density of light spots in the patterns to carry phase information. Two technical problems are(More)
We propose a novel dual-camera design to acquire 4D high-speed hyperspectral (HSHS) videos with high spatial and spectral resolution. Our work has two key technical contributions. First, we build a dual-camera system that simultaneously captures a panchromatic video at a high frame rate and a hyperspectral video at a low frame rate, which jointly provide(More)
—The one-to-one correspondence between co-occurrence image patches of two different resolutions is extensively used in example-based super-resolution (SR). Due to the dimensionality gap between low resolution (LR) and high resolution (HR) spaces, however, an LR patch may correspond to a number of HR patches in practice. This ambiguity is difficult to be(More)
This paper proposes a novel phase-shifting method for fast, accurate, and unambiguous 3D shape measurement. The basic idea is embedding a speckle-like signal in three sinusoidal fringe patterns to eliminate the phase ambiguity, but without reducing the fringe amplitude or frequency. The absolute depth is then recovered through a robust region-wise voting(More)