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标题: Evaluation of Radiometric Camera Response Recovery Methods [打印本页]

作者: 彬彬 时间: 2011-12-29 08:59
标题: Evaluation of Radiometric Camera Response Recovery Methods
1 Introduction

The camera response function determines the relationship between

the incident light on the camera sensor and the output pixel values

that are produced. For most consumer cameras, this function is proprietary

and needs to be estimated to create HDR images that accurately

represent the light distribution of the captured scene. Several

methods have been proposed in the literature to estimate this unknown

mapping using multiple exposures techniques. In this study,

we compare three of the most commonly used methods namely

Debevec and Malik’s [1997], Mitsunaga and Nayar’s [1999], and

Robertson et al.’s [2003] response curve estimation algorithms in

terms of how precisely they estimate an unknown camera response.

2 Comparison

We implemented all three algorithms in C++ using the exact procedures

outlined in the respective papers. We selected around 300

distinct sample positions from the uniform regions of the individual

exposures. In that we had 9 exposures, this amounted to a total of

2700 samples. We ensured that we had at least one sample for every

intensity level and the samples are not clumped together. A representative

set of samples is shown in Figure 1. As Mitsunaga and Nayar’s

algorithm does not have a weighting mechanism to underplay

the influence of under- and over-exposed samples, we discarded the

samples outside the range [5; 250] only for that algorithm.

The recovered response curves of a Canon EOS 550D using three

of the studied algorithms are shown on the right of Figure 1. As this

figure shows, the response curves are not only different from each

other but they also deviate significantly from the sRGB gamma. To

evaluate the fidelity of each algorithm, we devised the metric

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