Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

1677 results about "Pixel pair" patented technology

Driving Device for Display Panel, Display Device Including the Driving Device, Method for Driving a Display Panel, Program, and Storage Medium

A display panel is the one in which a pixel composed of sub-pixels of red (R), green (G), blue (B), and at least one other color has two sub-pixels at least in a vertical scanning direction, and color filters are provided respectively corresponding to the sub-pixels. There are provided: an incoming signal interpolating section which interpolate each of pixels based on incoming color signal components of red (R), green (G), and blue (B) at least in a vertical scanning direction to generate interpolated RGB signals; a luminance signal converting section which converts color signals of interpolated sub-pixels, which are obtained from the incoming signal interpolating section, into luminance signals; an another color luminance component adding section which adds a luminance signal component of at least one other color on a basis of luminance signal components of colors of red (R), green (G), and blue (B), which components are outputted from the luminance signal converting section; and a luminance reallocating section which reallocates luminance signals of peripheral interpolated sub-pixels, for a color of each of the color filters corresponding to the sub-pixels, in accordance with output from the another color luminance component adding section.
Owner:SHARP KK

Mura phenomenon compensation method of display panel and display panel

The embodiment of the invention discloses a mura phenomenon compensation method of a display panel. The method comprises the steps of compressing an area interval with n*m pixels, and storing a preset mura compensation value corresponding to one of first pixels in each area; according to a compensation value of the preset mura, conducting linear interpolation calculation to obtain mura compensation values of other pixels except the first pixel in the same area, and conducting mura compensation on the display panel; after the display panel conducts the mura compensation, obtaining information that a mura phenomenon still exists in the Xth area, wherein the Xth area belongs to the area formed by compressing the area interval with n*m pixels of the display panel; obtaining a final gray-scale compensation curve formula; according to the preset mura compensation value and the final gray-scale compensation curve formula, calculating supplementary mura compensation values corresponding to other pixels except the first pixel in the Xth area; conducting mura compensation on the Xth area again. The embodiment of the invention further discloses the display panel. By adopting the mura phenomenon compensation method of display panel and the display panel, the mura phenomenon compensation method of the display panel has the advantages that nonuniform brightness of a picture of the display panel can be alleviated.
Owner:SHENZHEN CHINA STAR OPTOELECTRONICS TECH CO LTD

Brain MRI (magnetic resonance image) segmentation method based on improved fuzzy C-means clustering algorithm

The invention relates to a brain MRI (magnetic resonance image) segmentation method based on an improved fuzzy C-means clustering algorithm. The method comprises steps that 1, initial classification is carried through utilizing the fuzzy C-means clustering algorithm; 2, the clustering quantity c, a fuzzy factor m, an algorithm iteration stop threshold Epsilon, the maximum iteration times max, a neighborhood window size and other artificial setting parameters are given; 3, a similarity matrix W of two pixels is calculated; 4, similarity rhoki of pixel pair types is calculated; 5, a membership matrix U is updated; 6, if ||U(t+1)-U(t)||<Epsilon, or t=max, iteration stops, U(t+1) is outputted, otherwise t=t+1, and the process turns to the step 4; and 7, for U(t+1), the maximum membership algorithm is employed to carry out deblurring operation, and label distribution is carried out to accomplish image segmentation. Through the method, three-portion optimization including improving a clustering center mode, introducing the partial space information and utilizing the intuitionistic fuzzy set information is accomplished, effects of noise resistance enhancement and segmentation precision improvement are realized, and an actual problem of high-precision segmentation for a brain MRI is solved.
Owner:BEIHANG UNIV

Adaptive noise intensity video denoising method and system thereof

The invention discloses an adaptive noise intensity video denoising method which is based on motion detection and is embedded in an encoder. The method comprises the following steps: (1) taking a sum of regularization frame differences in a neighborhood as an observed value, dividing input pixels into a static pixel and a dynamic pixel and using filters in different supporting domains for the two kinds of the pixels, wherein a filtering coefficient is adaptively determined according to noise intensity and an image local characteristic; (2) taking a single DCT coefficient or the sum of the several DCT coefficients as the characteristic, using AdaBoost as a tool to construct a cascade-form classifier and using the classifier to select a static block; (3) establishing a function model of connection between DCT coefficient distribution parameters of the video noise intensity and the static block and using the model to estimate the noise signal standard difference. By using noise intensity estimation embedded in the video encoder and a noise reduction technology provided in the invention, few computation costs can be used to acquire the parameters and the information needed by noise filtering. A time efficiency is good. Because a reliable clue is used to determine whether the pixels accord with a static hypothesis, the filter of the invention can effectively filter the noise and simultaneously maintain marginal sharpness of the static image. And motion blur caused by filtering in a motion area can be avoided.
Owner:ZHEJIANG GONGSHANG UNIVERSITY

Depth image autoegistration method combined with texture information

A depth image automatic registration process combining with texture information is mainly used to reconstruct the three-dimensional model of various actual objects, which comprises the steps: firstly extracting a texture image from scanning data or generating a texture image according a depth image, secondly extracting interest pixels in the texture image based on the characteristics of SIFT, and finding out candidate sets therein matched with the interest pixels through the crosscheck method, thirdly finding out correct matched pixel pairs in the candidate sets according to geometry information constraint, fourthly finding out matched apex pairs corresponding to the matched pixel pairs in a three-dimensional space, and calculating the rigid replacement matrix between two depth images, fifthly optimizing the result through using the improved ICP algorism, sixthly dividing the input sequences of several depth images into a plurality of bar type subsequences based on the registrations of two depth images, finally combining the subsequences through the strategy of forward searching, and constructing an integral three-dimensional model. The invention can fast register large-scale three-dimensional scanning data to generate a three-dimensional model, and has strong anti-noise capability and excellent universality.
Owner:BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products