Fast tone mapping for high dynamic range images

Thakur, S. K.; Sivasubramanian, M.; Nallaperumal, Krishnan; Karthikeyan, Marappan; Vishwanath, N.

doi:10.1109/iccic.2013.6724300

Cited by 11 publications

(11 citation statements)

References 9 publications

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“…Each (20) and Eq. (22). The method can calculate all equations of the TMO with only fixed-point arithmetic by these branching, approximation, and tables.…”

Section: Fixed-point Implementationmentioning

confidence: 99%

“…However, executing a TMO with fixed-point arithmetic is difficult due to the wide range value of HDR images. On the other hand, fast tone mapping functions were proposed in [19][20][21][22][23][24]. The authors in [19,20] focus on speeding up of the trilateral filter-based HDR tone mapping technique.…”

Section: Introductionmentioning

confidence: 99%

“…However, it still takes a long time for processing because the trilateral filter-based technique itself is heavy. In [21,22], visibility and contrast are simply controlled with a single parameter. Nevertheless, it does not directly contribute to reducing resources, and tone mapping functions for this approach is limited to a specific one.…”

Section: Introductionmentioning

confidence: 99%

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[Invited Paper] An Efficient Unified-Tone-Mapping Operation for HDR Images with Various Formats

Kiya

Dobashi

2016

MTA

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This paper addresses a unified tone mapping operation (TMO) for HDR images with fixed-point arithmetic. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image by compressing its dynamic range. A unified TMO can perform tone mapping for various HDR image formats with a single common TMO. 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, the method which allows to replace a floating-point number with two 8-bit integer numbers was proposed. However, this method has a limitation of available input HDR image formats. The proposed unified TMO can be applied for various formats such as the RGBE and the OpenEXR by introducing an intermediate format. Moreover, the method can conduct all calculations in the TMO with fixed-point arithmetic. By 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 the proposed method reduces the computational and memory cost, and gives almost same quality of LDR images, compared to the conventional method with floating-point arithmetic.

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“…Each (20) and Eq. (22). The method can calculate all equations of the TMO with only fixed-point arithmetic by these branching, approximation, and tables.…”

Section: Fixed-point Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

[Invited Paper] An Efficient Unified-Tone-Mapping Operation for HDR Images with Various Formats

Kiya

Dobashi

2016

MTA

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show abstract

“…However, executing a TMO with fixed-point arithmetic is difficult due to the wide range value of HDR images. On the other hand, fast tone mapping functions were proposed in [17][18][19][20]. The authors in [17,18] focus on speeding up of the trilateral filter-based HDR tone mapping technique.…”

mentioning

confidence: 99%

“…However, it still takes a long time for processing because the trilateral filter-based technique itself is heavy. In [19,20], visibility and contrast are 1 https://www.cambridge.org/core/terms. https://doi…”

mentioning

confidence: 99%

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

Dobashi

Atsushi

Iwahashi

et al. 2014

SIP

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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.

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A Unified Tone Mapping Operation for HDR Images Including Both Floating-Point and Integer Data

Dobashi

Iwahashi

Kiya

2015

Lecture Notes in Computer Science

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Fast tone mapping for high dynamic range images

Abstract: We present a fast, effective

Cited by 11 publications

References 9 publications

[Invited Paper] An Efficient Unified-Tone-Mapping Operation for HDR Images with Various Formats

[Invited Paper] An Efficient Unified-Tone-Mapping Operation for HDR Images with Various Formats

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

A Unified Tone Mapping Operation for HDR Images Including Both Floating-Point and Integer Data

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