Channel (digital image)

About: Channel (digital image) is a research topic. Over the lifetime, 7211 publications have been published within this topic receiving 69974 citations.

Augmented stereoscopic visualization for a surgical robot using a captured fluorescence image and captured stereoscopic visible images

Abstract: An illumination channel, a stereoscopic optical channel and another optical channel are held and positioned by a robotic surgical system. A first capture unit captures a stereoscopic visible image from the first light from the stereoscopic optical channel while a second capture unit captures a fluorescence image from the second light from the other optical channel. An intelligent image processing system receives the captured stereoscopic visible image and the captured fluorescence image and generates a stereoscopic pair of fluorescence images. An augmented stereoscopic display system outputs a real-time stereoscopic image comprising a three-dimensional presentation of a blend of the stereoscopic visible image and the stereoscopic pair of fluorescence images.

LAM: luminance attenuation map for photometric uniformity in projection based displays

Abstract: Large-area multi-projector displays show significant spatial variation in color, both within a single projector's field of view and across different projectors. Recent research in this area has shown that the color variation is primarily due to luminance variation. Luminance varies within a single projector's field of view, across different brands of projectors and with the variation in projector parameters. Luminance variation is also introduced by overlap between adjacent projectors. On the other hand, chrominance remains constant throughout a projector's field of view and varies little with the change in projector parameters, especially for projectors of the same brand. Hence, matching luminance response of all the pixels of a multi-projector display should help us to achieve photometric uniformity.In this paper, we present a method to do a per channel per pixel luminance matching. Our method consists of a one-time calibration procedure when a luminance attenuation map (LAM) is generated. This LAM is then used to correct any image to achieve photometric uniformity. In the one-time calibration step, we first use a camera to measure the per channel luminance response of a multi-projector display and find the pixel with the most "limited" luminance response. Then, for each projector, we generate a per channel LAM that assigns a weight to every pixel of the projector to scale the luminance response of that pixel to match with the most limited response. This LAM is then used to attenuate any image projected by the projector.This method can be extended to do the image correction in real time on traditional graphics pipeline by using alpha blending and color look-up-tables. To the best of our knowledge, this is the first effort to match luminance across all the pixels of a multi-projector display. Our results show that luminance matching can indeed achieve photometric uniformity.

System and method for generating a multi-dimensional image

Abstract: A system and method for generating a multi-dimensional image of an object in a scene is disclosed. One inventive aspect includes a spectral estimation module configured to convert a two-dimensional (2D) high-resolution light intensity image of the scene to a spectral-augmented image of a selected channel. The system further includes a high-resolution depth image generation module configured to generate a high-resolution depth image of the object based on a three-dimensional (3D) low-resolution depth image of the scene and the spectral-augmented image.