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标题: High Dynamic Range Images for Enhancing Low Dynamic Range Content [打印本页]

作者: 彬彬    时间: 2012-1-3 10:32
标题: High Dynamic Range Images for Enhancing Low Dynamic Range Content
Abstract

This poster presents a practical system for enhancing the quality

of Low Dynamic Range (LDR) videos using High Dynamic Range

(HDR) background images. Our technique relies on the assumption

that the HDR information is static in the video footage. This

assumption can be valid in many scenarios where moving subjects

are the main focus of the footage and do not have to interact with

moving light sources or highly reflective objects. Another valid

scenario is teleconferencing via webcams, where the background is

typically over-exposed, not allowing the users to perceive correctly

the environment where the communication is happening.

CR Categories:

I.4.1 [Image Processing and Computer Vision]: Enhancement—

Filtering I.3.3 [Computer Graphics]: Picture/Image Generation—

Bitmap and framebuffer operations

Keywords: High Dynamic Range, HDR videos, HDR acquisition,

LDR Enhancement

1 The Acquisition Method

HDR images capturing is now a well known and solved problem

in many conditions, see Banterle et al. [Banterle et al. 2011] for an

overview. However, HDR video cameras are currently under release,

but their cost make them affordable only for specific highstandard

applications, like cinematography or research. On the

other side, HDR images can be obtained with an SLR camera using

automatic exposure bracketing programs.

Our approach can be exploited in different scenarios such as: the

acquisition of high quality videos, and webcams teleconferencing

(where a trade-off between well-exposed subjects and background

is typically hard to find).

Our capturing method (see pipeline in Figure 2) consists of three

straightforward steps. Firstly, the scene’s background is acquired

in HDR, from dark to bright areas. Debevec and Malik’s method

[Banterle et al. 2011] is used to build a radiance map. Secondly,

an LDR video footage, where actors play in the scene, is acquired.

The exposure of this footage is well-exposed for the actors. Thirdly,

the background HDR image and the LDR image are processed by a

e-mail: banterle@isti.cnr.it

Figure 2: The proposed pipeline for augmenting LDR videos.

simple a linear blending algorithm.

One of the goals of the proposed method was to create a method

that could be used with a wide range of video-camera types. The

acquisition step is very simple, and the processing is fully automatic.

Hence, we decided to test the system using both a lowend

and a medium/high-end camera. In our experiments, we tested

our capturing technique with a Logitech QuickCam Pro 9000 and

a Canon 550D DSLR camera. The image in Figure 1 depicting

the reference HDR was tone mapped using Reinhard’s operator

implemented in [Banterle et al. 2011] (Additional videos can be

watched at the URL http://www.youtube.com/user/frabante). Regarding

timing, we ran our fully automatic enhancement algorithm

on an Intel Core 2 Duo at 2.33 Ghz equipped with 3Gb of memory,

a Geforce 9800 with 512Mb, and Windows 7. We implemented

our algorithm on the GPU, and it has real-time performances (more

than 24 FPS) when applied to full HD videos (1920  1080).

2 Conclusion

In this poster, we presented a simple, real-time and easy technique

for increasing the dynamic range of LDR videos using HDR

background images taken from the same camera and position. We

showed that this technique can produce convincing videos at low

cost.

References

BANTERLE, F., ARTUSI, A., DEBATTISTA, K., AND CHALMERS, A. 2011. Advanced

High Dynamic Range Imaging: Theory and Practice, first edition ed. AK

Peters, Ltd.
作者: C.R.CAN    时间: 2012-1-23 23:21
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作者: 菜刀吻电线    时间: 2012-3-2 23:27
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作者: 菜刀吻电线    时间: 2012-3-4 23:19
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作者: 奇    时间: 2012-3-19 23:18
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作者: 晃晃    时间: 2012-4-1 23:33
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作者: 菜刀吻电线    时间: 2012-4-4 23:21
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作者: tc    时间: 2012-12-1 23:27
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作者: 晃晃    时间: 2013-2-1 23:25
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作者: tc    时间: 2013-3-6 23:20
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