公开(公告)号：US10587897B2

公开(公告)日：2020-03-10

申请号：US15434699

申请日：2017-02-16

Applicant: Dolby Laboratories Licensing Corporation

Inventor： Sheng Qu ,  Peng Yin ,  Yan Ye ,  Yuwen He ,  Walter Gish ,  Guan-Ming Su ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N19/70 ,  H04N19/159 ,  H04N19/30 ,  H04N19/50 ,  H04N19/597 ,  H04N19/98 ,  H04L29/06

Abstract: Coding syntaxes in compliance with same or different VDR specifications may be signaled by upstream coding devices such as VDR encoders to downstream coding devices such as VDR decoders in a common vehicle in the form of RPU data units. VDR coding operations and operational parameters may be specified as sequence level, frame level, or partition level syntax elements in a coding syntax. Syntax elements in a coding syntax may be coded directly in one or more current RPU data units under a current RPU ID, predicted from other partitions/segments/ranges previously sent with the same current RPU ID, or predicted from other frame level or sequence level syntax elements previously sent with a previous RPU ID. A downstream device may perform decoding operations on multi-layered input image data based on received coding syntaxes to construct VDR images.

公开(公告)号：US10136162B2

公开(公告)日：2018-11-20

申请号：US14364979

申请日：2012-12-18

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Sheng Qu ,  Peng Yin ,  Yan Ye ,  Yuwen He ,  Walter Gish ,  Guan-Ming Su ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N7/50 ,  H04N21/2365 ,  H04N19/70 ,  H04N19/30 ,  H04N19/159 ,  H04N19/50 ,  H04N19/597 ,  H04N19/98 ,  H04L29/06

Abstract: Coding syntaxes in compliance with same or different VDR specifications may be signaled by upstream coding devices such as VDR encoders to downstream coding devices such as VDR decoders in a common vehicle in the form of RPU data units. VDR coding operations and operational parameters may be specified as sequence level, frame level, or partition level syntax elements in a coding syntax. Syntax elements in a coding syntax may be coded directly in one or more current RPU data units under a current RPU ID, predicted from other partitions/segments/ranges previously sent with the same current RPU ID, or predicted from other frame level or sequence level syntax elements previously sent with a previous RPU ID. A downstream device may perform decoding operations on multi-layered input image data based on received coding syntaxes to construct VDR images.

公开(公告)号：US09699483B2

公开(公告)日：2017-07-04

申请号：US15163613

申请日：2016-05-24

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N19/98 ,  H04N19/105 ,  H04N19/147 ,  H04N19/30 ,  H04N19/16 ,  H04N19/192

CPC classification number: H04N19/105 ,  G06F17/18 ,  H04N19/147 ,  H04N19/16 ,  H04N19/192 ,  H04N19/30 ,  H04N19/98

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

公开(公告)号：US09386313B2

公开(公告)日：2016-07-05

申请号：US14283845

申请日：2014-05-21

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N7/26 ,  H04N19/98 ,  H04N19/105 ,  H04N19/147 ,  H04N19/30 ,  H04N19/16 ,  H04N19/192

CPC classification number: H04N19/105 ,  G06F17/18 ,  H04N19/147 ,  H04N19/16 ,  H04N19/192 ,  H04N19/30 ,  H04N19/98

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and crosspixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

Abstract translation: 彩色图像预测是基于多通道多元回归（MMR）模型。 图像预测应用于高动态范围的图像和视频信号的有效编码。 MMR模型可以包括一阶参数，二阶参数和十字像素参数。 还提出了使用包含相邻像素关系的扩展参数的MMR模型。 使用最小均方误差准则，针对各种MMR模型提出了预测参数的闭合形式解。

公开(公告)号：US20140185930A1

公开(公告)日：2014-07-03

申请号：US14198470

申请日：2014-03-05

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar ,  Walter Gish

IPC: G06T5/50 ,  H04N19/136 ,  G06T5/00 ,  H04N19/186

CPC classification number: G06T5/50 ,  G06T5/009 ,  H04N1/6027 ,  H04N19/105 ,  H04N19/136 ,  H04N19/186 ,  H04N19/36

Abstract: Inter-color image prediction is based on color grading modeling. Prediction is applied to the efficient coding of images and video signals of high dynamic range. Prediction models may include a color transformation matrix that models hue and saturation color changes and a non-linear function modeling color correction changes. Under the assumption that the color grading process uses a slope, offset, and power (SOP) operations, an example non linear prediction model is presented.

公开(公告)号：US10021390B2

公开(公告)日：2018-07-10

申请号：US15608433

申请日：2017-05-30

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N19/15 ,  G06F17/18 ,  H04N19/192 ,  H04N19/98 ,  H04N19/105

CPC classification number: H04N19/105 ,  G06F17/18 ,  H04N19/147 ,  H04N19/16 ,  H04N19/192 ,  H04N19/30 ,  H04N19/98 ,  H05K999/99

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

公开(公告)号：US08837825B2

公开(公告)日：2014-09-16

申请号：US14198470

申请日：2014-03-05

Applicant: Dolby Laboratories Licensing Corporation

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar ,  Walter Gish

IPC: G06K9/36 ,  H04N19/186 ,  H04N19/105 ,  G06T5/50 ,  G06T5/00 ,  H04N19/136 ,  H04N19/36

CPC classification number: G06T5/50 ,  G06T5/009 ,  H04N1/6027 ,  H04N19/105 ,  H04N19/136 ,  H04N19/186 ,  H04N19/36

Abstract: Inter-color image prediction is based on color grading modeling. Prediction is applied to the efficient coding of images and video signals of high dynamic range. Prediction models may include a color transformation matrix that models hue and saturation color changes and a non-linear function modeling color correction changes. Under the assumption that the color grading process uses a slope, offset, and power (SOP) operations, an example non linear prediction model is presented.

Abstract translation: 彩色图像预测是基于颜色分级建模的。 预测应用于高动态范围的图像和视频信号的有效编码。 预测模型可以包括对色相和饱和度颜色变化进行建模的颜色变换矩阵和非线性函数建模颜色校正变化。 在颜色分级过程使用斜率，偏移和功率（SOP）操作的假设下，呈现示例非线性预测模型。

公开(公告)号：US10237552B2

公开(公告)日：2019-03-19

申请号：US15988937

申请日：2018-05-24

Applicant: DOLBY LABORATORIES LICENSING CORPORATION

Inventor： Guan-Ming Su ,  Sheng Qu ,  Hubert Koepfer ,  Yufei Yuan ,  Samir Hulyalkar

IPC: H04N19/105 ,  H04N19/147 ,  H04N19/30 ,  H04N19/16 ,  H04N19/192 ,  H04N19/98 ,  G06F17/18

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.