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5 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.

A texture filtering system

PendingCN122454011ASample ModeFilter system
The application relates to the technical field of integrated circuit design, in particular to a texture filtering system, which determines a filtering mode by combining a first preset condition with a detail level value, the first preset condition can be configured by a user, so that the user can flexibly adjust the filtering mode according to actual conditions, the flexibility of texture filtering is improved, and in any filtering mode, a sampling mode can be flexibly configured, the flexibility of texture filtering is further improved, and by combining a level evaluation value with a third preset condition, the sampling mode can be automatically modified in a specific scene, so that the consumption of GPU chip hardware resources by texture filtering is reduced, and the efficiency of texture filtering is improved.
Owner:METAX INTEGRATED CIRCUITS (SHANGHAI) CO LTD

A high-performance modular differentiable rendering method, apparatus, device, and storage medium based on DCU

This invention relates to the field of computer graphics technology, specifically to a high-performance modular differentiable rendering method, apparatus, device, and storage medium based on a Digital Core Utility (DCU). The method includes: initializing a modular rendering pipeline; placing rendering data in DCU memory in tensor form; performing geometric transformations on vertex coordinates and outputting homogeneous coordinates, with delayed perspective division; generating pixel-level geometric information through a multi-layered pipeline of triangle setup, layered binning, coarse rasterization, and fine rasterization; and performing rendering and gradient backpropagation through a pluggable, differentiable modular rendering pipeline composed of rasterization, attribute interpolation, texture filtering, anti-aliasing, and shading modules. This invention deeply optimizes the domestic DCU architecture, solving the problems of difficult porting, poor non-modular scalability, and coarse gradient approximation in existing technologies. It achieves high-performance, high-precision differentiable rendering on domestic hardware, significantly improving rendering speed, system flexibility, and 3D reconstruction convergence.
Owner:CHONGQING BITMAP INFORMATION TECH CO LTD

A global sparse texture filtering method based on edge structure preservation

ActiveCN119417721BImage enhancementThresholdingNon convex optimization
The application provides a global sparse texture filtering method based on edge structure preservation, including introducing a texture inhibition function in a penalty term, and constraining the gradient of an output image, the texture inhibition function inhibits texture, noise and unnecessary detail information in the image by setting two threshold values, then using the inhibited gradient as the input of the denominator of the penalty term, so that the penalty term can sufficiently distinguish texture and structure; sparse regular L1 norm is used to constrain the penalty term, non-convex optimization is converted into a convex optimization problem by introducing a sub-gradient, and an alternating direction multiplier method is used for iterative solution, so that better edge preservation is achieved; sparse L p Norm is used to constrain the penalty term and a preconditioned conjugate gradient method is used to accelerate and improve the calculation efficiency, so that more robust and sparse image smoothing effect is achieved. The application can improve the robustness of the algorithm in distinguishing texture and structure, retain better semantic information, and achieve better edge structure preservation and smoothing performance.
Owner:CHONGQING UNIV OF TECH