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

101 results about "Texture filtering" patented technology

In computer graphics, texture filtering or texture smoothing is the method used to determine the texture color for a texture mapped pixel, using the colors of nearby texels (pixels of the texture). There are two main categories of texture filtering, magnification filtering and minification filtering. Depending on the situation texture filtering is either a type of reconstruction filter where sparse data is interpolated to fill gaps (magnification), or a type of anti-aliasing (AA), where texture samples exist at a higher frequency than required for the sample frequency needed for texture fill (minification). Put simply, filtering describes how a texture is applied at many different shapes, size, angles and scales. Depending on the chosen filter algorithm the result will show varying degrees of blurriness, detail, spatial aliasing, temporal aliasing and blocking. Depending on the circumstances filtering can be performed in software (such as a software rendering package) or in hardware for real time or GPU accelerated rendering or in a mixture of both. For most common interactive graphical applications modern texture filtering is performed by dedicated hardware which optimizes memory access through memory cacheing and pre-fetch and implements a selection of algorithms available to the user and developer.

Marine internal wave detection algorithm based on multi-scale mathematical morphological feature fusion

InactiveCN109410228APreserve edge featuresEffectively eraseImage enhancementImage analysisPattern recognitionWavelet decomposition
The invention discloses a marine internal wave detection algorithm based on multi-scale mathematical morphological feature fusion, which comprises the following steps: multi-scale edge detection basedon wavelet transform modulus maximum obtains multi-scale edge information; the multi-scale edge detection obtains multi-scale edge information based on wavelet transform modulus maximum. Multi-scalemorphology is used to detect the edges of the low-frequency sub-images after wavelet decomposition. Then the small interference area is erased by using the connected domain method. Multi-scale waveletedge detection results of modulus maxima and multi-scale morphological edge detection results are fused to obtain multi-structure element multi-scale edge detection image. Compared with the existingtexture filtering method, the filtering result of the invention can not only keep the structure information of the image well, but also filter out some unnecessary texture details. The structure detection and the texture filtering algorithm provided by the invention obtain better effects in identifying and maintaining the weak gradient structure, inhibiting and smoothing the multi-scale and stronggradient texture and the like compared with the existing algorithm.
Owner:NANJING UNIV OF SCI & TECH

Texture filtering method and device based on anisotropy

InactiveCN102034262AAvoid oversampling3D-image renderingPattern recognitionLong axis
The invention provides a texture filtering method based on anisotropy, comprising the following steps of: carrying out MIP-MAP (Multum In Parvo Map) prefiltering on a texture image; considering an image in a screen space as a circle with a unit pixel as radius, projecting the pixel into the texture space and carrying out approximation by using an ellipse; calculating minor axis radius, macro axis radius and an included angle between the macro axis radius and a u-axis of the ellipse; determining a sampling layer L in a texture lookup table according to the calculated minor axis radius; determining the sample quantity in the sampling layer L and the positions of the macro axis sampling points along the ellipse according to the minor axis radius, the macro axis radius and the included angle between the macro axis radius and the u-axis, and sampling in the sampling layer L; sampling in a sampling layer L+1 along the macro axis of the ellipse according to the sampling quantity of the sampling layer L+1; carrying out linear interpolation on color values obtained from the sampling layer L and the sampling layer L+1 to finally obtain the color value. By adopting 1 / 4 sampling quantity in the L layer as the sampling quantity in the L+1 layer, the invention avoids oversampling and ensures that the texture can be still kept clear when the texture view angle is far away from the observation points.
Owner:BYD CO LTD
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