An accurate characterization method for a multispectral high-dynamic-range (HDR) imaging system is proposed by combining multispectral and HDR imaging technologies. The multispectral HDR imaging system, which can acquire the visible spectrum at many wavelength bands, can provide an accurate color reproduction and physical radiance information of real objects. An HDR camera is used to capture an HDR image without multiple exposures and a liquid crystal tunable filter (LCTF) is used to generate multispectral images. Due to its several limitations in the multispectral HDR imaging system, a carefully designed and an innovative characterization algorithm is presented by considering a logarithmic camera response of the HDR camera and different spectral transmittance of the LCTF. The proposed method efficiently and accurately recovers the full spectrum from the multispectral HDR images using a transformation matrix and provides device-independent color information (e.g., CIEXYZ and CIELAB). The transformation matrix is estimated by training the estimated sensor responses from a multispectral HDR imaging system and the reflectance measurements from a spectroradiometer using Moore–Penrose pseudoinverse matrix.
Metallic paint has been widely used to provide for special visual appearance to various products so that photorealistic rendering of this material has been an important issue in the development of new products. We introduce a new approach that predicts the reflectance of metallic paint while considering manufacturing parameters. Our main idea is to simulate the appearance of various metallic paints having different composition of constituent materials by combination of measured bidirectional reflectance distribution functions and thereby to find a paint that provides optimal appearance of a product with appropriate composition of constituent materials. We mainly focused on two paint parameters, average size and density of aluminum flakes, because they significantly affect the appearance of metallic paint. We also present a compact representation to approximate a large size of measured data using a few curve functions. We demonstrate the efficiency and usability of our reflectance estimation method using some examples.
This paper deals with a method to effectively compress the measured reflectance data of pearlescent paints. In
order to simulate the coated surface realistically, it is requested to measure the reflectance of the pearlescent
paints by using multiple wavelengths. The wavelength-based reflectance data requests a large amount of storage.
However, we can reduce the size of the measured BRDF and retain the accuracy the data by using several
factorization algorithms. In this paper, we analyze the decomposition of the measured BRDF of pearlescent
paint and find the number of lobes or basis functions to retain the visual accuracy of the measured reflectance.
Most recent bidirectional reflectance distribution function (BRDF) measurement systems are the image-based
that consist of a light source, a detector, and curved samples. They are useful for measuring the reflectance
properties of a material but they have two major drawbacks. They suffer from high cost of BRDF acquisition
and also give inaccurate results due to the limited use of spectral bands. In this paper, we propose a novel multispectral
HDR imaging system and its efficient characterization method. It combines two promising
technologies: high dynamic range (HDR) imaging and multispectral imaging to measure BRDF. We perform a
full spectral recovery using camera response curves for each wavelength band and its analysis. For this, we use
an HDR camera to capture HDR images and a liquid crystal tunable filter (LCTF) to generate multi-spectral
images. Our method can provide an accurate color reproduction of metameric objects as well as a saturated
image. Our multi-spectral HDR imaging system provides a very fast data acquisition time and also gives a low
system setup cost compared to previous multi-spectral imaging systems and point-based commercial spectroradiometers.
We verify the color accuracy of our multi-spectral HDR imaging system in terms of human vision
and metamerism using colorimetric and spectral metric.
The use of pearlescent paints has grown significantly for many industrial products, due to their special visual effect, which originates from optical interference between many small pearlescent platelets. This makes the visual appearance of pearlescent paints vary with the light and view direction. Since pearlescent paints are very sensitive to specific wavelength bands, multispectrum-based representation methods that use spectral distributions give us more accurate image synthesis of them than does the use of RGB-based ones. In this paper, we present a novel image-based goniospectrophotometer system and its characterization method to acquire the spectral bidirectional reflectance distribution functions (BRDFs) for realistic image synthesis of pearlescent paints by combining two promising technologies, namely, high-dynamic-range images and multispectral images. The capability of our system is demonstrated by generating rendering results from four different material samples and comparing them with the RGB-based results and fully measured BRDF data.
We present a novel high-dynamic-range (HDR) camera-based bidirectional reflectance distribution function (BRDF) measurement system that can measure the reflectance property of isotropic materials. Our developed system can measure the BRDF of highly specular materials much faster than previous systems. It measures highly dense BRDF samples for a wider reflection angle with less noise so that it provides accuracy that is necessary for computer graphics application. To estimate the reflectance of a given material, we perform an absolute photometric calibration for the HDR camera. Our system is verified by checking the Helmholtz reciprocity and comparing the performance with that of previous image-based systems. The capability and efficiency of the developed system is demonstrated by comparing the images generated by measure-and-fit and direct-rendering methods using the measured data of four different isotropic materials.
KEYWORDS: Bidirectional reflectance transmission function, High dynamic range imaging, Cameras, Light sources, Gold, Sensors, Data acquisition, Calibration, Metals, Imaging systems
We present a novel image-based BRDF (Bidirectional Reflectance Distribution Function) measurement system for
materials that have isotropic reflectance properties. Our proposed system is fast due to simple set up and automated
operations. It also provides a wide angular coverage and noise reduction capability so that it achieves accuracy that is
needed for computer graphics applications. We test the uniformity and constancy of the light source and the reciprocity
of the measurement system. We perform a photometric calibration of HDR (High Dynamic Range) camera to recover an
accurate radiance map from each HDR image. We verify our proposed system by comparing it with a previous imagebased
BRDF measurement system. We demonstrate the efficiency and accuracy of our proposed system by generating
photorealistic images of the measured BRDF data that include glossy blue, green plastics, gold coated metal and gold metallic paints.
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