High dynamic range image generation and rendering

Abstract

Techniques and tools for high dynamic range (HDR) image rendering and generation. An HDR image generating system performs motion analysis on a set of lower dynamic range (LDR) images and derives relative exposure levels for the images based on information obtained in the motion analysis. These relative exposure levels are used when integrating the LDR images to form an HDR image. An HDR image rendering system tone maps sample values in an HDR image to a respective lower dynamic range value, and calculates local contrast values. Residual signals are derived based on local contrast, and sample values for an LDR image are calculated based on the tone-mapped sample values and the residual signals. User preference information can be used during various stages of HDR image generation or rendering.

Description

technical field [0001] The technology relates to generating and rendering digital images, and more particularly, to generating and rendering high dynamic range digital images. Background technique [0002] In video and imaging systems, colors are typically represented as vector coordinates in a multidimensional "color space" with three or more channels. Common examples include the well-known classes of RGB and YUV color spaces. The RGB color space specifies pixel values ​​using coordinates representing the intensities of red, green, and blue light, respectively. The YUV color space specifies pixel values ​​using coordinates representing luminance or chrominance values. [0003] Currently, many image capture, processing, and display devices can handle only 256 (2 8 ) pixel values ​​with a small dynamic range of discrete values, and these 256 discrete values ​​are represented by 8 bits. These images can be described as having a "bit depth" of 8 bits. In a typical RGB digi...

AI Technical Summary

Problems solved by technology

Other values ​​(e.g. alpha or opacity values, brightness, etc.) may also be constrained by the low dynamic range limit

Images