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)
BACKGROUND Tinea capitis is a fungal infection of the scalp occurring commonly in children. Historical data indicate that clinical manifestations and the spectrum of etiologic agents vary greatly with geography, as well as socioeconomic affected populations. OBJECTIVE To study the possible connection between socioeconomic status, the disease patterns and(More)
Tinea capitis remains a common public health problem worldwide especially in developing areas. Aetiologic agents and clinical pattern vary with geography and history of socioeconomic conditions. Three community surveys and a prospective study were carried out over the past 50 years (1965-2014) in the Qingyunpu District of Nanchang, Southern China. Clinical(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)
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)
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)