Tone mapping

About: Tone mapping is a research topic. Over the lifetime, 1713 publications have been published within this topic receiving 48490 citations.

Method of compensating the color tone differences between two images of the same scene

Abstract: The color tone compensation method provides a simple and efficient method to compensate the color tone differences between two different sources of images. A first image sample, such as a still image, from a first image capturing source and a second image sample, such as a video frame, from a second image capturing source are aligned, and a tone-mapping estimation routine is applied to the two aligned images. The tone-mapping estimation routine uses the pixel intensity value histograms associated with the two aligned images and generates a tone mapping table. The tone mapping table includes a conversion intensity value for each intensity value in the second image. The conversion intensity value is a statistical measure, such as the mean, calculated according to the data in the corresponding pixel intensity value histogram. The tone-mapping table is applied to any image generated by the second image capturing source, thereby generating a new image with similar color tone as the first image generated by the first image capturing source.

Automatic level control for video cameras towards HDR techniques

Abstract: We give a comprehensive overview of the complete exposure processing chain for video cameras. For each step of the automatic exposure algorithm we discuss some classical solutions and propose their improvements or give new alternatives. We start by explaining exposure metering methods, describing types of signals that are used as the scene content descriptors as well as means to utilize these descriptors. We also discuss different exposure control types used for the control of lens, integration time of the sensor, and gain control, such as a PID control, precalculated control based on the camera response function, and propose a new recursive control type that matches the underlying image formation model. Then, a description of commonly used serial control strategy for lens, sensor exposure time, and gain is presented, followed by a proposal of a new parallel control solution that integrates well with tone mapping and enhancement part of the image pipeline. Parallel control strategy enables faster and smoother control and facilitates optimally filling the dynamic range of the sensor to improve the SNR and an image contrast, while avoiding signal clipping. This is archived by the proposed special control modes used for better display and correct exposure of both low-dynamic range and high-dynamic range images. To overcome the inherited problems of limited dynamic range of capturing devices we discuss a paradigm of multiple exposure techniques. Using these techniques we can enable a correct rendering of difficult class of high-dynamic range input scenes. However, multiple exposure techniques bring several challenges, especially in the presence of motion and artificial light sources such as fluorescent lights. In particular, false colors and light-flickering problems are described. After briefly discussing some known possible solutions for the motion problem, we focus on solving the fluorescence-light problem. Thereby, we propose an algorithm for the detection of fluorescent lights from the image itself and define a set of remedial actions, to minimize false color and light-flickering problems.

High dynamic range imaging & image-based lighting

Abstract: This class outlines recent advances in high dynamic range imaging (HDRI) - from capture to image-based lighting to display. In a hands-on approach, we show how HDR images and video can be captured, the file formats available to store them, and the algorithms required to prepare them for display on low dynamic range displays. The trade-offs at each step are assessed allowing attendees to make informed choices about data capture techniques, file formats and tone reproduction operators. In addition, the latest developments in image-based lighting will be presented.

Image dynamic range compression method, apparatus, and digital camera

Abstract: A method of compressing an original dynamic range of an original image, includes a first step of obtaining a reduced image corresponding to the original image by performing quantization and downsampling on the original image that has been input; a second step of calculating a look-up table based on the reduced image, wherein the look-up table indicates a mapping relationship between the original dynamic range of the original image and a dynamic range of a medium; and a third step of mapping each of the pixels in the original image from the original dynamic range of the original image onto the dynamic range of the medium based on the look-up table.

Parallel implementation of a real-time high dynamic range video system

Abstract: This article describes the use of the parallel processing capabilities of a graphics chip to increase the processing speed of a high dynamic range HDR video system. The basis is an existing HDR video system that produces each frame from a sequence of regular images taken in quick succession under varying exposure settings. The image sequence is processed in a pipeline consisting of: shutter speeds selection, capturing, color space conversion, image registration, HDR stitching, and tone mapping. This article identifies bottlenecks in the pipeline and describes modifications to the algorithms that are necessary to enable parallel processing. Time-critical steps are processed on a graphics processing unit GPU. The resulting processing time is evaluated and compared to the original sequential code. The creation of an HDR video frame is sped up by a factor of 15 on the average.