Subpixel rendering

About: Subpixel rendering is a research topic. Over the lifetime, 3885 publications have been published within this topic receiving 82789 citations.

Array substrate, display panel and display apparatus having the same, and driving method thereof

Abstract: An array substrate includes a base substrate; an array of a plurality of pixel units on the base substrate, each pixel unit including at least one subpixel for image display, at least some of the plurality of pixel units including a semiconductor photodetector in at least one subpixel for detecting biometric information; a plurality of first scan lines for driving image display; a plurality of second scan lines, each second scan line being connected to a row of subpixels having the semiconductor photodetector in a row of pixel units; and a plurality of read lines, each read line being connected to each semiconductor photodetector in a column of subpixels having the semiconductor photodetector in a column of pixel units

Displaying method and image display device

Abstract: In a displaying method for use in an image display, an original gray scale is divided into a higher gray scale and a lower gray scale. Further, the color subpixels are divided into two groups corresponding to the higher and lower gray scales, respectively. The gray scale to be expressed by each subpixel is calibrated by weighing the original higher or lower gray scale for the pixel and the adjacent pixels and summing up the results. The color shift problem due to different visual angles can therefore be solved.

Lensfree color imaging on a nanostructured chip using compressive decoding.

Abstract: We demonstrate subpixel level color imaging capability on a lensfree incoherent on-chip microscopy platform. By using a nanostructured substrate, the incoherent emission from the object plane is modulated to create a unique far-field diffraction pattern corresponding to each point at the object plane. These lensfree diffraction patterns are then sampled in the far-field using a color sensor-array, where the pixels have three different types of color filters at red, green, and blue (RGB) wavelengths. The recorded RGB diffraction patterns (for each point on the structured substrate) form a basis that can be used to rapidly reconstruct any arbitrary multicolor incoherent object distribution at subpixel resolution, using a compressive sampling algorithm. This lensfree computational imaging platform could be quite useful to create a compact fluorescent on-chip microscope that has color imaging capability.

A topological stereo matcher

Abstract: Presented here is a new stereo algorithm that produces dense, high-quality, subpixel disparity maps. It offers two improvements over previous algorithms. First, it does not blur disparity values across sharp changes in depth. Second, it can reconstruct the correct correspondence between two images even when there is substantial vertical displacement between them: this algorithm has been tested with rotations up to 10 degrees and vertical translations up to 16 pixels. Although such image pairs require extra processing time, this ability is vital when exact calibration cannot be maintained. The new algorithm depends on two new ideas. First, it exploits the fact that the correct vertical disparity field is due to camera misalignment and, thus, has only a few (significant) degrees of freedom. The algorithm passes camera alignment parameters, not raw disparity fields, between scales. Disparities at individual locations can diverge only slightly from this global model, greatly reducing the algorithm's search space. Second, the new algorithm uses a pre-match filter that prevents two patches of image from matching if they do not have the same (local) topological structure. This constraint subsumes previous “figural continuity” proposals and can be checked by simple, local operations. The filter seems to improve the algorithm's ability to select the correct match from many alternatives and it suppresses intermediate values near sharp changes in disparity. This technique can be extended to other matching tasks, such as motion tracking, analyzing texture periodicity, and evaluating the performance of edge finders.

Subpixellic Methods for Sidelobes Suppression and Strong Targets Extraction in Single Look Complex SAR Images

Abstract: Synthetic aperture radar (SAR) images display very high dynamic ranges. Man-made structures (like buildings or power towers) produce echoes that are several orders of magnitude stronger than echoes from diffusing areas (vegetated areas) or from smooth surfaces (e.g., roads). The impulse response of the SAR imaging system is, thus, clearly visible around the strongest targets: sidelobes spread over several pixels, masking the much weaker echoes from the background. To reduce the sidelobes of the impulse response, images are generally spectrally apodized, trading resolution for a reduction of the sidelobes. This apodization procedure (global or shift-variant) introduces spatial correlations in the speckle-dominated areas that complicates the design of estimation methods. This paper describes strategies to cancel sidelobes around point-like targets while preserving the spatial resolution and the statistics of speckle-dominated areas. An irregular sampling grid is built to compensate the subpixel shifts and turn cardinal sines into discrete Diracs. A statistically grounded approach for point-like target extraction is also introduced, thereby providing a decomposition of a single look complex image into two components: a speckle-dominated image and the point-like targets. This decomposition can be exploited to produce images with improved quality (full resolution and suppressed sidelobes) suitable both for visual inspection and further processing (multitemporal analysis, despeckling, interferometry).