Tone mapping

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

High Dynamic Range Image Analysis through Various Tone Mapping Techniques

Abstract: image quality is improved drastically with the increase of the technology. The conventional display devices may not be suitable for these High dynamic range images. The tone mapping is the process to show the good quality image in the normal LDR display devices. This paper presents a review of the tone mapping algorithms. It provides the methodology on Tone Mapped Image Quality Index (TMIQI) and the Blind Quality Assessment of Tone-Mapped Images (BTMQI). The region is basically expanded and compressed to visualize properly. Thereby the region-enhanced pseudo-exposures are fused into an HDR image. The image quality of BTMQI is comparatively higher than the TMIQI method. The low dynamic range images are suitable to both the conventional and advance display devices. Keywordsdynamic range imaging, structural preservation, tone mapping, perceptual image processing, structural similarity

Application-Specific Tone Mapping Via Genetic Programming

Abstract: High dynamic range (HDR) imagery permits the manipulation of real-world data distinct from the limitations of the traditional, low dynamic range (LDR), content. The process of retargetting HDR content to traditional LDR imagery via tone mapping operators (TMOs) is useful for visualising HDR content on traditional displays, supporting backwards-compatible HDR compression and, more recently, is being frequently used for input into a wide variety of computer vision applications. This work presents the automatic generation of TMOs for specific applications via the evolutionary computing method of genetic programming (GP). A straightforward, generic GP method that generates TMOs for a given fitness function and HDR content is presented. Its efficacy is demonstrated in the context of three applications: visualisation of HDR content on LDR displays, feature mapping and compression. For these applications, results show good performance for the generated TMOs when compared to traditional methods. Furthermore, they demonstrate that the method is generalisable and could be used across various applications that require TMOs but for which dedicated successful TMOs have not yet been discovered.

Real-Time High Fidelity Inverse Tone Mapping for Low Dynamic Range Content

Abstract: In this paper, we present a novel parallel implementation of a high fidelity inverse tone mapping operator. Our method makes use of point based graphics to accelerate density estimation, and multi-core CPUs for extracting light sources. We show that our method can achieve real-time performance on a lower-end graphics card, with minimum loss of quality.

Single exposure vs tone mapped High Dynamic Range images: A study based on quality of experience

Abstract: Tone mapping operators (TMOs), employed to fit the dynamic range of High Dynamic Range (HDR) visual signals to that of the display, are generally non-transparent and modify the visual appearance of the scene. Despite this, tone mapped content generally tends to have more visual details as compared to a single exposure scene. It is however not clear if the extra details in tone mapped HDR affect user preferences over a single exposure content in terms of scene appearance and to what extent. This paper aims to shed light on this issue via a comprehensive subjective study. Our results reveal that there is no statistical evidence to establish if the users preferred tone mapped content over the single exposure version as closer representation of the corresponding HDR scene. We present those results as well as outline the possible factors contributing to this somewhat unexpected finding.

A fixed-point implementation of tone mapping operation for HDR images expressed in floating-point format

Abstract: A tone mapping operation (TMO) for HDR images with fixed-point arithmetic is proposed. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image by compressing its dynamic range. Since HDR images are generally expressed in a floating-point data format, a TMO also deals with floating-point data even though resulting LDR images have integer data. As a result, conventional TMOs require many resources such as computational and memory cost. To reduce the resources, an integer TMO which treats a floating-point number as two 8-bit integer numbers was proposed. However, this method has the limitation of available input HDR image formats. The proposed method introduces an intermediate format to relieve the limitation of input formats, and expands the integer TMO for the intermediate format. The proposed integer TMO can be applied for multiple formats such as the RGBE and the OpenEXR. Moreover, the method can conduct all calculations in the TMO with fixed-point arithmetic. Using both integer data and fixed-point arithmetic, the method reduces not only the memory cost, but also the computational cost. The experimental and evaluation results show that the proposed method reduces the computational and memory cost, and gives almost same quality of LDR images, compared with the conventional method with floating-point arithmetic.