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Jason A Klivington

from Portland, OR
Age ~55
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Also known as:
Jason Alexis Klivington, Livingston K Jason
Phone and address:
1218 SE 53Rd Ave, Portland, OR 97215
Connected to:
Brian H Klix, 38Charles F Klix, 67James L Klix, 91John A Klix, 44Candace C Klixbull, 46Mary E Kliza, 69Nancy G Kliza, 76Aleksandar Kljaic, 31Jelena Kljajic, 47Mirela Kljajic, 35

Jason Klivington Phones & Addresses

  • 1218 SE 53Rd Ave, Portland, OR 97215
  • 4513 21St Ave, Portland, OR 97211
  • 1007 15Th Ave, Portland, OR 97214 (503) 230-1888
  • Westport, CT

Skills

R&D • Computation • Software

Industries

Computer Software

Resumes

Resumes

Jason Klivington Photo 1

Jason Klivington

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Location:
Portland, OR
Industry:
Computer Software
Skills:
R&D
Computation
Software

Publications

Us Patents

Dynamic Selection Of Field/Frame-Based Mpeg Video Encoding

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US Patent:
7145952, Dec 5, 2006
Filed:
Jan 7, 2002
Appl. No.:
10/041750
Inventors:
Jason Klivington - Portland OR, US
Assignee:
Apple Computer, Inc. - Cupertino CA
International Classification:
H04B 1/66
US Classification:
3752402, 37524024, 37524023, 37524026, 382250, 382246, 348206
Abstract:
A discrete cosine transform (DCT) level enhancement to Motion Picture Experts Group (MPEG) video encoding is described that results in a more concise bitstream than MPEG encoding without the enhancement. One degree of freedom provided by the MPEG encoding specifications is whether a frame- or field-based DCT operation will be used. In the field-based DCT operations, luminance sub-blocks are built from even or odd rows of the original image, which correspond to the top and bottom fields in field-based video. This allows the encoder to take advantage of the higher correlation between rows for the same field, especially in field-based video with a high level of motion. In one embodiment, both field- and frame-based DCT operations are performed and the results are quantized. On a macroblock-by-macroblock basis, the option that results in the fewest non-zero coefficients is selected and those coefficients are used for run-time encoding.

Fractal-Dithering Technique For Image Display

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US Patent:
7206001, Apr 17, 2007
Filed:
Jun 22, 2004
Appl. No.:
10/874796
Inventors:
Richard E Crandall - Portland OR, US
Evan T Jones - Portland CA, US
Jason Klivington - Portland OR, US
Assignee:
Apple Computer, Inc. - Cupertino CA
International Classification:
G09G 5/02
US Classification:
345596, 345690
Abstract:
Rapid dithering of an RGB image from a higher order to a lower order number of bits is provided while introducing fewer undesirable artifacts than are visible in conventional dithering technology. A compact, deterministic method enables the elimination of banding, for example as is seen in 24-bit monitors when viewing color images with greater color depth. A fractal dithering engine selects a threshold matrix appropriate for an input stream, and using the threshold matrix, dithers images of the input stream to output images having a lower order number of color bits. In one embodiment, the threshold matrix is obtained by traversing 2-by-2 sub-regions of an N-by-N matrix according to a traversal pattern, and then applying a reverse binary function to the values in the original matrix to yield the threshold matrix. The threshold matrix preferably tessellates the pixel plane, subject to certain constraints.

Generation And Use Of Masks In Mpeg Video Encoding To Indicate Non-Zero Entries In Transformed Macroblocks

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US Patent:
7548583, Jun 16, 2009
Filed:
Aug 9, 2005
Appl. No.:
11/200949
Inventors:
Jason Klivington - Portland OR, US
Assignee:
Apple Inc. - Cupertino CA
International Classification:
H04B 1/66
US Classification:
3752402
Abstract:
During Motion Picture Experts Group (MPEG) video encoding a two-dimensional discrete cosine transform (DCT) is performed on data representing an original image. The resulting coefficients are then quantized, which typically results in many zero coefficients. Because of the nature of most video data, most higher-order coefficients are typically zero and the lower-order coefficients (i. e. , those grouped towards the upper left of the matrix) are more likely to be non-zero. To reduce the lengths of runs among the lower-order coefficients, the coefficients can be encoded in a zig-zag pattern. In one embodiment, the zig-zag pattern is maintained and one or more masks are generated based on the output of the quantization phase. The one or more masks are used to identify the coefficients within the matrix that are non-zero. This reduces the number of accesses to memory required to encode the non-zero coefficients and runs of zero coefficients.

Fast Lossless Encoder For Digitized Analog Data

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US Patent:
7643693, Jan 5, 2010
Filed:
Apr 16, 2004
Appl. No.:
10/826927
Inventors:
Richard E Crandall - Portland OR, US
Evan T Jones - Portland OR, US
Jason Klivington - Portland OR, US
Mitchell Oslick - Mountain View CA, US
Assignee:
Apple Inc. - Cupertino CA
International Classification:
G06K 9/36
G06K 9/46
US Classification:
382244, 382166, 382238
Abstract:
Lossless compression and the corresponding decompression of image and audio data are enabled using a combination of dynamic prediction and Golomb coding. First, data is converted from the RGB domain into the YUV domain. Next, a dynamic prediction algorithm is run to express pixel values as differential values rather than original bit values. Prediction coefficients are re-evaluated on the fly enabling additional compression because of more accurate predictors. An Adaptive Golomb Engine next performs an additional compression step, using an adaptive form of Golomb encoding in which mean values are variable across the data. The use of variable mean values reduces the deleterious effects found in conventional Golomb encoding in which localized regions of similar data are inefficiently coded if their bit values are uncommon in the data as a whole.

Arbitrary-Resolution, Extreme-Quality Video Codec

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US Patent:
7751475, Jul 6, 2010
Filed:
Jun 22, 2004
Appl. No.:
10/875058
Inventors:
Richard E Crandall - Portland OR, US
Evan T Jones - Portland OR, US
Jason Klivington - Portland OR, US
David Kramer - Santa Clara CA, US
Assignee:
Apple Inc. - Cupertino CA
International Classification:
H04N 7/12
H04N 11/02
US Classification:
37524003, 37524019
Abstract:
Image data to be compressed is first converted from the RGB domain into a gamma-powered YUV domain. A wavelet transform then separates image data into high- and low-detail sectors, incorporating a dynamic scaling method, allowing for optimal resolution. The output data from the wavelet transform is then quantized according to an entropy-prediction algorithm that tightly controls the final size of the processed image. An adaptive Golomb engine compresses the data using an adaptive form of Golomb encoding in which mean values are variable across the data. Using variable mean values reduces the deleterious effects found in conventional Golomb encoding in which localized regions of similar data are inefficiently coded if their bit values are uncommon in the data as a whole. Inverse functions are applied to uncompress the image, and a fractal dithering engine can additionally be applied to display an image on a display of lower color depth.

Digital Image Resampling

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US Patent:
8520971, Aug 27, 2013
Filed:
Sep 30, 2010
Appl. No.:
12/895764
Inventors:
Richard E. Crandall - Portland OR, US
Jason Alexis Klivington - Portland OR, US
Rudolph van der Merwe - Portland OR, US
Mark Alan Zimmer - Aptos CA, US
Assignee:
Apple Inc. - Cupertino CA
International Classification:
G06K 9/32
US Classification:
382266, 382299, 345698
Abstract:
Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Arbitrary-Resolution, Extreme-Quality Video Codec

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US Patent:
20100322305, Dec 23, 2010
Filed:
May 24, 2010
Appl. No.:
12/785692
Inventors:
Richard Eugene Crandall - Portland OR, US
Evan T. Jones - Portland OR, US
Jason Klivington - Portland OR, US
David A. Kramer - Santa Clara CA, US
Assignee:
APPLE INC. - Cupertino CA
International Classification:
H04N 7/24
US Classification:
37524003, 375E07226
Abstract:
Image data to be compressed is first converted from the RGB domain into a gamma-powered YUV domain. A wavelet transform then separates image data into high- and low-detail sectors, incorporating a dynamic scaling method, allowing for optimal resolution. The output data from the wavelet transform is then quantized according to an entropy-prediction algorithm that tightly controls the final size of the processed image. An adaptive Golomb engine compresses the data using an adaptive form of Golomb encoding in which mean values are variable across the data. Using variable mean values reduces the deleterious effects found in conventional Golomb encoding in which localized regions of similar data are inefficiently coded if their bit values are uncommon in the data as a whole. Inverse functions are applied to uncompress the image, and a fractal dithering engine can additionally be applied to display an image on a display of lower color depth.

Automatic Image Sharpening

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US Patent:
20130084019, Apr 4, 2013
Filed:
Sep 30, 2011
Appl. No.:
13/250989
Inventors:
Richard E. Crandall - Portland OR, US
Jason Alexis Klivington - Portland OR, US
Rudolph van der Merwe - Portland OR, US
International Classification:
G06K 9/40
US Classification:
382255
Abstract:
Systems, methods and computer program products are disclosed for automatic image sharpening. Automatic image sharpening techniques are disclosed that automatically bring a blurred image into focus. Techniques for reducing edge ringing in sharpened images are also disclosed. According to implementations, a computer-implemented method includes determining a normalized entropy of a first image, calculating a correlation target based on the normalized entropy, automatically determining a blur radius of a de-convolution kernel that causes a cosine of a first radial power spectrum of the kernel and a second radial power spectrum of a reconstruction of the first image to approximate the correlation target and generating a second image based on the blur radius.
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Jason A Klivington from Portland, OR, age ~55 Get Report