Bo Zhang - Westford MA, US Ashish Koul - Cambridge MA, US Olivier Francois Joseph Harel - Mountain View CA, US
Assignee:
Broadcom Corporation - Irvine CA
International Classification:
G06K 9/48 G06K 9/40
US Classification:
382199, 382254, 382260, 382275
Abstract:
De-ringing operation for image processing. A selective image processing means is presented herein by which high frequency content is preserved while also eliminating ringing within digital images, and this is achieved without introducing aliasing. Based on the analysis of neighboring pixels, one or more of multiple filter modules and/or multiple image filtering/rocessing means is/are selectively applied to generate an output sample for a given pixel location. Two measures (e. g. , local activity (LA) and edge strength (ES)) are calculated based on processing at least two different groups of pixels near a desired output sample. One of these groups of pixels may be a subset of another of the groups of pixels. By analyzing these two measures (e. g. , LA and ES), selective processing of pixels near the desired output location ensures that high frequency content within the digital image is preserved with substantially reduced and/or eliminated ringing therein.
Christopher Payson - Bolton MA, US Timothy Hellman - Concord MA, US Ashish Koul - Cambridge MA, US
Assignee:
Broadcom Corporation - Irvine CA
International Classification:
H04N 5/14 H04N 9/74
US Classification:
348571, 348590
Abstract:
A video processing device may process video input comprising a plurality of streams, wherein images corresponding to at least some of the plurality of streams may be displayed concurrently. The video processing device may determine, prior to processing of a pixel in one of the plurality of streams whether the pixel comprises one or more keyed video parameters; and if the pixel comprises at least one keyed parameter, one or more other pixels may be selected, and a video parameter corresponding to the at least one keyed video parameter of the pixel may be generated based on the selected one or more other pixels. The generated video parameter may then be utilized instead of the at least one keyed video parameter during the processing of the pixel. This may comprise luma and/or chroma based scaling. Outputs of the processing of the pixel may be post-processed, by clamping at least one of the video parameters.
Method And System For Rate Control In A Video Encoder
Ashish Koul - Cambridge MA, US Douglas Chin - Haverhill MA, US Stephen Gordon - North Andover MA, US
International Classification:
H04N 11/04
US Classification:
375240010
Abstract:
Described herein is a method and system for rate control in a video encoder. The method and system can use relative persistence and intensity of video data in a macroblock to classify that macroblock. On a relative basis, a greater number of bits can be allocated to persistent video data with a low intensity. The quantization is adjusted accordingly. Adjusting quantization prior to video encoding enables a corresponding bit allocation that can preserve perceptual quality.
Method And System For Scene Change Detection In A Video Encoder
Described herein is a method and system for rate estimation in a video encoder. The method and system use a motion estimation metric to determine the position of a scene change. The average of the motion estimation metric is computed for a set of pictures. When change in the motion estimation metric average exceeds a threshold, a scene change is declared. Declaration of a scene change prior to video encoding enables a corresponding bit allocation that can preserve perceptual quality.
Method And System For Testing Rate Control In A Video Encoder
Ashish Koul - Cambridge MA, US Douglas Chin - Haverhill MA, US
International Classification:
H04N 11/04 H04B 1/66 H04N 11/02 H04N 7/12
US Classification:
375240030
Abstract:
Described herein is a method and system for testing rate control in a video encoder. The method and system can use relative persistence and intensity of video data in a macroblock to classify that macroblock. On a relative basis, a greater number of bits can be allocated to persistent video data with a low intensity. The quantization is adjusted accordingly. Adjusting quantization prior to video encoding enables a corresponding bit allocation that can preserve a bit rate requirement.
A method for encoding pictures within a groups of pictures using prediction, where a first reference picture from a group of pictures and a second reference pictures from the subsequent group of pictures are used in predicting pictures in the group of pictures associated with the first reference picture. A plurality of anchor pictures in the group of pictures associated with the first reference picture may be predicted using both the first and second reference pictures to ensure a smooth transition between different groups of pictures within a video frame.
Christopher Payson - Bolton MA, US Timothy Hellman - Concord MA, US Ashish Koul - Cambridge MA, US
Assignee:
Broadcom Coproration - Irvine CA
International Classification:
H04N 5/14
US Classification:
348604, 348E05062
Abstract:
A video processing device can determine whether an input pixel includes a keyed video parameter prior to filtering the input pixel. A non-keyed substitute pixel can be generated for the input pixel that includes the keyed video parameter. The non-keyed substitute pixel can be filtered if the input pixel included the keyed video parameter, otherwise the input pixel can be filtered.
Massachusetts Institute of Technology 2001 - 2003
M.Eng., Electrical Engineering and Computer Science
Massachusetts Institute of Technology 1997 - 2001
S.B., Electrical Engineering and Computer Science
Skills:
Signal Processing Project Management Product Development Business Strategy Embedded Software Data Analysis Operations Management Management Consulting Cross Functional Team Leadership Digital Image Processing Video Compression Soc
Credit Suisse
Assistant Vice President
Hudson Data Llc Dec 2007 - Oct 2009
Senior Consultant
Viteos Fund Services Nov 2006 - Jun 2007
Intern
Education:
New York University - Polytechnic School of Engineering 2005 - 2007
Skills:
Fixed Income Equities Prime Brokerage Business Analysis Financial Modeling Sdlc Capital Markets Risk Management Investment Banking Valuation Middle Office Finance Corporate Finance Hedge Funds Strategy Sql Banking Requirements Analysis Business Development Business Strategy Derivatives
Sandy; Posted 2004-02-15T20:52:39Z; Ashish is my favorite tall, skinny Kashimiri in all the east coast. He's a wonderful friend, a great listener and will make you
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