US2014169473A1PendingUtilityA1

Texture sensitive temporal filter based on motion estimation

Assignee: MICROSOFT CORPPriority: Feb 26, 2008Filed: Nov 11, 2013Published: Jun 19, 2014
Est. expiryFeb 26, 2028(~1.6 yrs left)· nominal 20-yr term from priority
H04N 19/82H04N 19/139H04N 19/85H04N 19/513H04N 19/00896H04N 19/00684
51
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Claims

Abstract

Architecture that employs texture sensitive temporal filtering to reuse motion estimation information in a realtime encoder. The temporal filter is applied for classified static areas. The architecture reuses the motion estimation results on motion vectors, cost estimates (e.g., sum of absolute difference (SAD)), and edge awareness texture information to apply the temporal filter on the current picture. Filtering can be applied at the pixel level, block level or macroblock level.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . An encoder system, comprising:
 a motion estimation component for generating frame characteristics and a motion vector of an input frame; and   a filter component for filtering a frame characteristics map of the frame characteristics and outputting a filtered frame to an encoding process.   
     
     
         2 . The system of  claim 1 , further comprising a mapping component for generating a frame characteristics map based on the motion vector and the frame characteristics. 
     
     
         3 . The system of  claim 2 , wherein the motion estimation component, the mapping component and the filter component are part of an encoder. 
     
     
         4 . The system of  claim 1 , wherein the frame characteristics include one or more of a cost function, variance information, or texture information. 
     
     
         5 . The system of  claim 4 , wherein the cost function is a sum of absolute differences (SAD) cost function. 
     
     
         6 . The system of  claim 1 , wherein the frame characteristics map is a static map or a dynamic map. 
     
     
         7 . The system of  claim 1 , wherein the frame characteristics are defined at the pixel level. 
     
     
         8 . A computer-implemented encoding system, comprising:
 a motion estimation component for generating a motion vector, cost function, and texture data from an input frame;   a detection component for creating a map of frame characteristics based on the motion vector, cost function, and texture data;   a filter component for filtering the frame characteristics map and outputting a filtered frame; and   an encoding component for encoding the motion vector and the filtered input frame to output a compressed frame.   
     
     
         9 . The system of  claim 8 , wherein the motion estimator component includes a cost component that employs a SAD cost function 
     
     
         10 . The system of  claim 8 , wherein the detection component includes a predetermined threshold that defines if the map is static or dynamic. 
     
     
         11 . The system of  claim 8 , wherein the motion estimation component codes the frame characteristics of the input frame as a block that is inter-block or intra-block. 
     
     
         12 . A computer-implemented method of encoding a picture, comprising:
 generating motion estimation results of a motion vector, a cost associated with the motion vector, and texture information from a motion estimation process of input video information;   creating a map based on detection of one or more of the motion estimation results, the cost, and the texture information;   filtering the map temporally to output a filtered input frame; and   encoding the filtered input frame and the motion vector to output a compressed representation of the input video information.   
     
     
         13 . The method of  claim 12 , wherein the texture information includes edge awareness information. 
     
     
         14 . The method of  claim 12 , further comprising applying the filtering on a block basis according to a static map. 
     
     
         15 . The method of  claim 12 , wherein the map is created for each block of a current frame based on the motion vector, the cost, and the texture information. 
     
     
         16 . The method of  claim 12 , further comprising pre-generating a texture threshold for different cost functions. 
     
     
         17 . The method of  claim 12 , further comprising filtering the map when a block counter exceeds a threshold value, the threshold indicating the map is static. 
     
     
         18 . The method of  claim 12 , further comprising applying weights across multiple frames as part of filtering the map. 
     
     
         19 . The method of  claim 12 , further comprising coding a block of the input video information as intra-block or inter-block based on motion estimation. 
     
     
         20 . The method of  claim 19 , further comprising employing block variance as the textual information for intra-block.

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