Hui-Liang Shen

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A scanner characterization method is proposed to estimate spectral reflectance from scanner responses by using an optimized adaptive estimation method. In contrast to our previous study [J. Opt. Soc. Am. A21, 1125 (2004)], this method considers the weighting of training samples. It is demonstrated that the color accuracy of this method is only slightly(More)
For dielectric inhomogeneous objects, the perceived reflections are the linear combinations of diffuse and specular reflection components. Specular reflection plays an important role in the fields of image analysis, pattern recognition, and scene synthesis. Several methods for the separation of the diffuse and the specular reflection components have been(More)
In multispectral imaging system, one of the most important tasks is to accurately reconstruct the spectral reflectance from system responses. We propose such a new method by combing three most frequently used techniques, i.e., wiener estimation, pseudo-inverse, and finite-dimensional modeling. The weightings of these techniques are calculated by minimizing(More)
In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The(More)
Two methods for colorimetric characterization of color scanner are proposed based on the measures of perceptual color difference error. The first method is used to minimize the total color differences between the actual and predicted color samples. The second one, which is a generalization of the existing cubic-root pre-processing technique, derives the(More)
Out-of-focus blur occurs frequently in multispectral imaging systems when the camera is well focused at a specific (reference) imaging channel. As the effective focal lengths of the lens are wavelength dependent, the blurriness levels of the images at individual channels are different. This paper proposes a multispectral image deblurring framework to(More)