High dynamic range imaging on mobile devices

Bilcu, Radu Ciprian; Burian, A.; Knuutila, A.; Vehviläinen, Markku

doi:10.1109/icecs.2008.4675101

Cited by 22 publications

(13 citation statements)

References 11 publications

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“…Similar algorithms are presented in [3,6], but they have different ways for calculation of coefficients, by using appropriate weighting functions, as it is mentioned earlier. Proposed algorithm for HDR-like scene-mapped imaging performs calculations on the global image level.…”

Section: Description Of the Methodsmentioning

confidence: 90%

“…Currently, standard digital cameras are mostly limited to capturing only 8-bit or 12-bit images, which do not cover the full dynamic range of luminosity in the real world. This can be improved by: (a) capturing multiple standard images and then merging them into an HDR image [3,6,8,11,15], or (b) using special image sensors, such as oversampled image sensor [1]. The possibility of taking a number of exposures of the same scene to capture details from very dark regions to very bright regions was proposed in [11].…”

Section: Related Workmentioning

confidence: 99%

“…An algorithm for extending dynamic range on mobile devices is proposed in [3]. Implemented algorithm takes three images (one whose exposure time is calculated using the standard camera auto-exposure algorithm, and two additional whose exposure times are calculated) and merge them into a final image using coefficients obtained from weighting function.…”

Section: Related Workmentioning

confidence: 99%

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Method for HDR-like imaging using industrial digital cameras

Popadić

Todorović

Reljin

2016

Multimed Tools Appl

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Dynamic range of the scene can be significantly wider than the dynamic range of an image because of limitations of A/D conversion. In such a situation, numerous details of the scene cannot be adequately shown on the image. Standard industrial digital cameras are equipped with an auto-exposure function that automatically sets both the aperture value and cameras exposure time. When measuring a scene with atypical distribution of light and dark elements, the indicated auto-exposure time may not be optimal. The aim of work was to improve, with minimal cost, the performance of standard industrial digital cameras. We propose a low complexity method for creating HDRlike image using three images captured with different exposure times. The proposed method consists of three algorithms: (1) algorithm for estimating whether the autoexposure time is optimal, (2) algorithm which determines exposure times for two additional images (one with shorter and another with longer than auto-exposure time), and (3) algorithm for HDR-like imaging based on fusion of three previously obtained images. Method is implemented on FPGA inserted into standard industrial digital camera. Results show that the proposed approach produces high quality HDR-like scene-mapped 8-bit images with minimal computational cost. All improvements may be noticed through the performance evaluation.

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Section: Description Of the Methodsmentioning

confidence: 90%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Method for HDR-like imaging using industrial digital cameras

Popadić

Todorović

Reljin

2016

Multimed Tools Appl

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“…The multi-frame processing (MFP) algorithms have been wide- ly exploited because of the development of image processing. It utilizes the relevance between the multiple frames to get a better image, like the high-dynamic-range (HDR) image fusion [7]. The HDR image is synthesized from multiple lowdynamic-range (LDR) images with different exposure settings.…”

Section: A Introduction Of Multi-frame Processing Algorithmsmentioning

confidence: 99%

Coarse-grained reconfigurable image stream processor architecture for high-definition cameras and camcorders

Cheng

Chen

Jason

et al. 2010

2010 International SoC Design Conference

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The coarse-grained reconfigurable image stream processor (CRISP) architecture is introduced for the image processing demands of high-definition (HD) cameras and camcorders. With several architectural concepts of the reconfigurable architecture, the CRISP architecture is proposed to meet the performance and flexibility requirements of the HD cameras. A multi-frame processing system with CRISP is implemented to achieve the real-time HD video recording and 11M-pixel image processing capability. Compared with the performance of the high-dynamic-range image fusion algorithm implemented with a general-purpose processor, 106 times speed-up is achieved by the proposed processor with high image quality of 42.5dB in PSNR.

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“…Most of the work that address HDR on mobile devices are recent [6][7][8] and their main goal is mainly on capturing HDR image or video using the built-in digital camera. There are some TMO 9 that were developed to take in account different display devices on the generation of the tone mapped image, including the mobile devices displays.…”

Section: Introductionmentioning

confidence: 99%

A survey on HDR visualization on mobile devices

et al. 2012

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There is a vast body of literature concerning the capture, storing, transmission and display of High Dynamic Range (HDR) imaging. Nevertheless, there are few works that try to address the problem of getting HDR on mobile devices. Their hardware limitations, such as processing power, storage space, graphics capabilities and screen characteristics, transform that problem in a big challenge. However, since more and more HDR content is being produced and given that in a few years it can become a standard, it is necessary to provide the means to visualize HDR images and video on mobile devices. The main goal of this paper is to present a survey on HDR visualization approaches and techniques developed specifically for mobile devices. To understand what are the main challenges that need to be addressed in order to visualize HDR on mobile devices, an overview of their main characteristics is given. The very low dynamic range of most of mobile devices' displays implies that a tone mapping operator (TMO) must be applied in order to visualize the HDR content. The current status of the research on TMO will be presented and analyzed, a special attention will be given to the ones that were developed taking in account the limited characteristics of the mobile devices' displays. Another important issue is visualization quality assessment, meaning visualize HDR content without losing the main characteristics of the original HDR content. Thus, evaluation studies of HDR content visualization on mobile devices will be presented and their results analyzed.

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High dynamic range imaging on mobile devices

Cited by 22 publications

References 11 publications

Method for HDR-like imaging using industrial digital cameras

Method for HDR-like imaging using industrial digital cameras

Coarse-grained reconfigurable image stream processor architecture for high-definition cameras and camcorders

A survey on HDR visualization on mobile devices

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