Tone mapping

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

Visual saliency-based tone mapping image quality evaluation method

Abstract: The invention discloses a visual saliency-based tone mapping image quality evaluation method. A multi-scale structure fidelity measurement is combined with statistical naturalness measurement, the saliency characteristic of a human visual system is considered in a calculation process, and the quality of different regions in an image is weighted by using a visual saliency map, so the evaluation result is more close to a subjective evaluation result of a person. The algorithm can be used for evaluating the quality of the tone mapping quality converted from a high dynamic range into a low dynamic range, the advantages and disadvantages of a tone mapping operator are measured, and the method is embedded into the tone mapping operator to provide a basis for operator optimization and parameter setting.

Product review: high dynamic range displays

Abstract: In the natural world, the human eye is confronted with a wide range of colors and luminances. A surface lit by moonlight might have a luminance level of around 10-3 cd/m2, while surfaces lit during a sunny day could reach values larger than 105 cd/m2. A good quality CRT (cathode ray tube) or LCD (liquid crystal display) monitor is only able to achieve a maximum luminance of around 200 to 300 cd/m2 and a contrast ratio of not more than two orders of magnitude. In this context the contrast ratio or dynamic range is defined as the ratio of the highest to the lowest luminance. We call high dynamic range (HDR) images, those images (or scenes) in which the contrast ratio is larger than what a display can reproduce. In practice, any scene that contains some sort of light source and shadows is HDR. The main problem with HDR images is that they cannot be displayed, therefore although methods to create them do exist (by taking multiple photographs at different exposure times or using computer graphics 3D software for example) it is not possible to see both bright and dark areas simultaneously. (See Figure 1.) There is data that suggests that our eyes can see detail at any given adaptation level within a contrast of 10,000:1 between the brightest and darkest regions of a scene. Therefore an ideal display should be able to reproduce this range. In this review, we present two high dynamic range displays developed by Brightside Technologies (formerly Sunnybrook Technologies) which are capable, for the first time, of linearly displaying high contrast images. These displays are of great use for both researchers in the vision/graphics/VR/ medical fields as well as professionals in the VFX/gaming/ architectural industry.

Analysis of Smoothed LHE Methods for Processing Images with Optical Illusions

Abstract: To replicate human visual perception, we analyze processing images with optical illusion using edge preserving filters and smoothed local histogram equalization (LHE). Images with the optical illusions are good models for gradual/rapid changes in contrast and strong edges, which are good cases for assessing the robustness of image filters. Here, we study and an-alyze the performance of smoothed LHE filters while processing perceptual illusion. Our studies conclude that, smoothed LHEs are useful in retaining actual edge forms in these images as they can operate using large kernel sizes. These large kernel size filters can construct sawtooth like edge and it corresponds to adequately wide halos. We also demonstrate the usefulness of smoothed LHE like tone mapping techniques in preserving naturalness, and we confirmed it by performing subjective visual test.

Explorable Tone Mapping Operators

Abstract: Tone-mapping plays an essential role in high dynamic range (HDR) imaging. It aims to preserve visual information of HDR images in a medium with a limited dynamic range. Although many works have been proposed to provide tone-mapped results from HDR images, most of them can only perform tone-mapping in a single pre-designed way. However, the subjectivity of tone-mapping quality varies from person to person, and the preference of tone-mapping style also differs from application to application. In this paper, a learning-based multimodal tone-mapping method is proposed, which not only achieves excellent visual quality but also explores the style diversity. Based on the framework of BicycleGAN, the proposed method can provide a variety of expert-level tone-mapped results by manipulating different latent codes. Finally, we show that the proposed method performs favorably against state-of-the-art tone-mapping algorithms both quantitatively and qualitatively.

Ram-based tone mapping for high dynamic range images

Abstract: In this paper we present a novel tone mapping algorithm for high dynamic range (HDR) images using the retinal adaptation model (RAM). The physiological evidence suggests that the RAM is obtained by measuring intensity-response functions to flashes of light presented under varying adaptation conditions, which leads to a theoretic-sound model that can be flexibly adapted for tone reproduction. The multiplicativesubtractive process of the model can provide high quality tone mapping results for rendering the HDR images. The experimental results demonstrate that our RAM-based tone mapping approach is effective to produce pleasing results on HDR images in a wide range of real-world scenarios.