Dolby Laboratories Licensing Corporation

Walter Christian Gish

Christopher J Vogt

Samir N Hulyalkar

Guan-Ming Su

Sheng Qu

David Ruhoff

Yan Ye

Alexandros Michael Tourapis

Jon S McElvain

Zhen Li

Hubert Koepfer

Yufei Yuan

Peng Yin

Yuwen He

Tao Chen

Robin Atkins

Gregory John Ward

Hyung-Suk Kim

Donald Pian

Jonathan Robert Miller

Scott J Daly

Kimball Darr Thurston, Iii

Michael J Rockwell

Jon Scott Mcelvain

Walter C Vogt

Richard W Webb

A method for generating a high-dynamic-range (HDR) image includes (a) denoising a short-exposure-time image, wherein the denoising comprises applying a first guided filter to the short-exposure-time image, the guided filter utilizing a long exposure-time-image as its guide, (b) after the step of denoising, scaling at least one of the short-exposure-time image and the long-exposure-time image to place the short-exposure-time image and the long-exposure-time image on a common radiance scale, and (c) after the step of scaling, merging the short-exposure-time image with the long-exposure-time image to generate the HDR image.

High-dynamic-range image generation with pre-combination denoising

The quantization parameter QP is well-known in digital video compression as an indication of picture quality. Digital symbols representing a moving image are quantized with a quantizing step that is a function QSN of the quantization parameter QP, which function QSN has been normalized to the most significant bit of the bit depth of the digital symbols. As a result, the effect of a given QP is essentially independent of bit depth a particular QP value has a standard effect on image quality, regardless of bit depth. The invention is useful, for example, in encoding and decoding at different bit depths, to generate compatible, bitstreams having different bit depths, and to allow different bit depths for different components of a video signal by compressing each with the same fidelity (i.e., the same QP).

Quantization control for variable bit depth

An auto exposure method for a spatially-multiplexed-exposure (SME) high-dynamic-range (HDR) image sensor includes (a) retrieving raw image data from an exposure of the spatially-multiplexed-exposure high-dynamic-range image sensor, (b) preprocessing long-exposure pixel values and short-exposure pixel values of the raw image data to remove therefrom long-exposure pixel values and short-exposure pixel values failing to meet one or more quality requirements, (c) synthesizing, into an high-dynamic-range histogram, the long-exposure pixel values remaining after the step of preprocessing and the short-exposure pixel values remaining after the step of preprocessing, (d) deriving a goodness metric from the high-dynamic-range histogram, (e) adjusting at least one of the long exposure time and the short exposure time, based at least in part upon the goodness metric, and (f) outputting the at least one of the long exposure time and the short exposure time, as adjusted, to the spatially-multiplexed-exposure high-dynamic-range image sensor.

Auto exposure of spatially-multiplexed-exposure high-dynamic-range image sensor metric and adjustment

An auto exposure method for an image sensor includes (a) evaluating variance, for each of a plurality of histograms of the pixel values from a respective plurality of individual exposures of the image sensor at respective exposure 5 time settings, of contribution from individual bins of the histogram to total entropy of the histogram, to determine an optimal exposure time for the image sensor corresponding to a minimum value of the variance, and (b) outputting the optimal exposure time to the image sensor.

Auto exposure of image sensors based upon entropy variance

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.

Specifying visual dynamic range coding operations and parameters

In layered Visual Dynamic range (VDR) coding, inter-layer prediction requires several color-format transformations between the input VDR and Standard Dynamic Range (SDR) signals. Coding and decoding architectures are presented wherein inter-layer prediction is performed in the SDR-based color format, thus reducing computational complexity in both the encoder and the decoder, without compromising coding efficiency or coding quality.

Efficient architecture for layered VDR coding

Enhancing image dynamic range is described. An input video signal that is represented in a first color space with a first color gamut, which is related to a first dynamic range, is converted to a video signal that is represented in a second color space with a second color gamut. The second color space is associated with a second dynamic range. At least two (e.g., three) color-related components of the converted video signal are mapped over the second dynamic range.

Extending image dynamic range

Novel methods and systems for image processing and gamut mapping are disclosed, where image parameters in a first color space are transformed into parameters in a second color space. In one example, the gamut mapping system processes the image parameters in a parametrized space using substantially rectangular spectral functions. In another example, the gamut mapping system processes the image parameters in a parametrized space using smooth spectral functions. The smooth spectral functions may include a linear combination of functions, including at least a cosine square function. Image parameters may include an intensity parameter, a center wavelength parameter, and a saturation parameter.

Gamut mapping systems and methods

Techniques use multiple lower bit depth (e.g., 8 bits) codecs to provide higher bit depth (e.g., 12+ bits) high dynamic range images from an upstream device to a downstream device. Multiple layers comprising a base layer and one or more enhancement layers may be used to carry video signals comprising image data compressed by lower bit depth encoders to a downstream device, wherein the base layer cannot be decoded and viewed on its own. Lower bit depth input image data to base layer processing may be generated from higher bit depth high dynamic range input image data via advanced quantization to minimize the volume of image data to be carried by enhancement layer video signals. The image data in the enhancement layer video signals may comprise residual values, quantization parameters, and mapping parameters based in part on a prediction method corresponding to a specific method used in the advanced quantization. Adaptive dynamic range adaptation techniques take into consideration special transition effects, such as fade-in and fade-outs, for improved coding performance.

Layer decomposition in hierarchical VDR coding

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Oak Park, CA, United States of America

Walter Christian Gish