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Fundamentals of image analysis and interpretation
Published in Michael O’Byrne, Bidisha Ghosh, Franck Schoefs, Vikram Pakrashi, Image-Based Damage Assessment for Underwater Inspections, 2019
Bidisha Ghosh, Michael O’Byrne, Franck Schoefs, Vikram Pakrashi
Combining images can be done using various merging algorithms such as the one developed by Debevec and Malik (1997). Their algorithm relied on knowing the response function of the digital camera, which is the relationship between the physical light intensity reaching a pixel (on the sensor of the camera) and the intensity that appears in the image. With the response function, multiple photographs could then be merged into a single, high dynamic range radiance map, with the pixel values being proportional to the true radiance values in the scene. The code to create HDR images in MATLAB® is shown below. Since HDR images cannot be properly displayed on a display with limited dynamic range, tone mapping is employed to reduce the dynamic range, or contrast ratio, of the entire image, while retaining localized contrast.
Tone Mapping
Published in Francesco Banterle, Alessandro Artusi, Kurt Debattista, Alan Chalmers, Advanced High Dynamic Range Imaging, 2017
Francesco Banterle, Alessandro Artusi, Kurt Debattista, Alan Chalmers
Tone mapping is the operation that adapts the dynamic range of HDR content to suit the lower dynamic range available on a given display. This reduction of the range attempts to keep some characteristics of the original content such as local and global contrast, details, etc. Furthermore, it is often desired that the perception of the tone mapped image should match the perception of the real-world scene; see Figure 3.1. Tone mapping is performed using an operator f or tone mapping operator (TMO), which is defined in general as f(I)Riω×h×c→Doω×h×c, $$ f(I)\,{\mathbb{R}}_{i}^{{\omega \times h \times c}} \to {\mathbb{D}}_{o}^{{\omega \times h \times c}} , $$
A comparative review of different TMOs for HDR images
Published in Rajesh Singh, Anita Gehlot, Intelligent Circuits and Systems, 2021
To display HDR images in conventional manner using LDR displays tone mapping operators play a prominent role. To display HDR images more realistically and accurately there is a need for efficient and effective TMOs though already existing TMOs such as Benterle, gamma correction, Raman are Chiu are developed and put to use. Luminance, mPSNR, MSE, TMQI and FSITM, which are considered to be the performance, are recorded while calculating for existing tone mapping operators. Compared to other tone mapping operators, promising results can be achieved using gamma TMO.
Regional Differences in the Perception of Daylit Scenes across Europe Using Virtual Reality. Part I: Effects of Window Size
Published in LEUKOS, 2022
Claudia Moscoso, Kynthia Chamilothori, Jan Wienold, Marilyne Andersen, Barbara Matusiak
However, in the case of brightness, evaluations of this particular attribute in a VR setting have to be interpreted with care due to the limitations of current static tone-mapping algorithms, especially if a scene consists of large bright and dark areas. In general, a tone-mapping algorithm applies typical human brightness perception to an image and reduces the high contrast of an HDR image to a displayable image with low contrast. Currently available tone-mapping algorithms, when applied to 360° rendered scenes, compress the dynamic range of the entire 360° image once, whereas in the real world the eye would adapt to the different luminance levels in a scene depending on the viewing direction. Therefore, the tone-mapped scene would deviate more from real-world perception the more the luminance levels differ between the bright and dark areas. An adaptive tone-mapping depending on the viewing direction would probably address this issue. However, for the current study, where only a static tone-mapping algorithm is applied, as discussed in Section 2, the aforementioned limitations between VR and real-world perception apply. This effect might influence different window sizes differently, as well as different spaces. However, analysis of the influence of regions on the brightness perception deliver valid results since the participants were exposed to the same stimuli.
Window Size Effects on Subjective Impressions of Daylit Spaces: Indoor Studies at High Latitudes Using Virtual Reality
Published in LEUKOS, 2021
Claudia Moscoso, Kynthia Chamilothori, Jan Wienold, Marilyne Andersen, Barbara Matusiak
However, in the case of brightness, evaluations of this particular attribute in a VR setting have to be interpreted with care due to the limitations of current static tone-mapping algorithms, especially if a scene consists of large bright and dark areas. In general, a tone-mapping algorithm applies typical human brightness perception to an image and reduces the high contrast of an HDR image to a displayable image with low contrast. Currently available tone-mapping algorithms, when applied to 360° rendered scenes, compress the dynamic range of the entire 360° image once, whereas in the real world the eye would adapt to the different luminance levels in a scene depending on the viewing direction. Therefore, the tone-mapped scene would deviate more from real world perception the more the luminance levels differ between the bright and dark areas. An adaptive tone-mapping depending on the viewing direction would probably address this issue. However, for the current study, where only a static tone-mapping algorithm is applied, as discussed in Section 2.2.3, the aforementioned limitations apply. To highlight these limitations, as well as the restricted generalizability of findings related to brightness evaluations, results regarding this attribute will be reported separately.
Lossless Compression of Hyperspectral Imagery by Assimilating Decorrelation and Pre-processing with Efficient Displaying Using Multiscale HDR Approach
Published in IETE Journal of Research, 2022
A. S. Anand Swamy, A. S. Mamatha, N. Shylashree, Vijay Nath
High Dynamic Range (HDR) images capture more information of the natural environment than normal Low Dynamic Range images (LDR) using higher bits with floating-point data type [12,13]. Unfortunately, the HDR images are not displayable on modern display devices which are low dynamic range devices. The operation called Tone Mapping is used for reducing the dynamic range while preserving the information to be displayed on LDR devices [14–18]. Edge preserving filters are prominently used in the decomposition of the HDR images into base layers and detail layers [19–30]. Motivated by techniques of HDR, visualization of Hyperspectral images was examined in [31] and [32].