M. J. Vrhel and H. J. Trussell, "Filter considerations in color correction," IEEE Trans. Image Proc., vol. 3, no. 2, pp. 147--161, Mar. 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....This correction is equivalent to a regression estimate for simulated camera RGB values under tungsten for the Macbeth chart to CIE tristimulus values under D65. As the data set is known to be the Macbeth Chart, we chose to use this fact in the color correction procedure. Our method is based on [11]. The average absolute error between the real and simulated values is very low for the and values (0.0189 and 0.0193 out of maximum values of 0.6991 and 0.7044 respectively; corresponding to 2.7 and 2.74 , respectively) and slightly higher for the values (0.0887 out of a maximum value of 1.3548 ....

M. J. Vrhel and H. J. Trussell, "Filter considerations in color correction," IEEE Trans. Image Processing, vol. 3, pp. 147--161, Mar. 1994.

....results are yet available 3 Marimont and Wandell[MW92] have shown that this task is a much easier than recovering the full spectral reflectance curves since cone responses for surfaces measured across illuminants are approximately a linear transform apart. In related research Vrhel and Trussell[VT94] have derived the optimal camera curves for surface colour recovery (assuming that illuminant change is linear) Future research: Colorimetric measurement is a very time consuming process. Typically devices such as spectrophotometers and colorimeters are used. These devices are expensive and have ....

M.J. Vrhel and H.J. Trussell. Filter considerations in color correction. IEEE Transactions on Image Processing, 1994.

.... about the statistical distributions of surface colors in the scene, Buchsbaum [6] assumes that the average of the surface reflectances over the entire scene is gray (the gray world assumption) Gershon [19] assumes that the average scene reflectance matches that of another known color; Vrhel [47] assumes knowledge of the general covariance structure of the illuminant, given a small set of illuminants, and Freeman [16] assumes that the illumination and reflection in a scene follow known probability distributions. These methods are effective when the distribution of colors within the scene ....

M.J. Vrhel and H.J. Trussell, "Filter considerations in color correction" IEEE Transactions on Image Processing, 3:147-161, 1994.

....response of the DCS 200 to an independently acquired image. This prediction error was also small. 1 Introduction To process data from digital color cameras, it is often necessary to know the spectral response properties of the camera s sensors. For example, many demosaicing [1] color correction [13] and illuminant estimation algorithms [4, 5] require this knowledge. In addition, the intrinsic color quality of an image depends on the spectral characteristics of the sensors [2, 7, 12, 14, 15] used. Thus an important component of characterizing a digital color camera is measuring its sensor ....

Vrhel, M. J., and Trussell, H. J., `Filter Considerations in Color Correction', IEEE Transactions on Image Processing, Vol. 3, No. 2, pp. 147-161, Mar. 1994.

....about the statistical distributions of surface colors in the scene, Buchsbaum [5] assumes that the average of the surface reflectances over the entire scene is gray (the gray world assumption) Gershon [16] assumes that the average scene reflectance matches that of some other known color. Vrhel [42]assumes knowledge of the general covariance structure of the illuminant, given a small set of illuminants. Similarly, Freeman [13] assumes that the illumination and reflection in a scene follow known probability distributions. These methods are effective when the distribution of colors within the ....

M.J. Vrhel and H.J. Trussell, "Filter considerations in color correction" IEEE Transactions on Image Processing, 3:147-161, 1994.

....about the statistical distributions of surface colors in the scene, Buchsbaum [1] assumes that the average of the surface reflectances over the entire scene is gray (the gray world assumption) Gershon [12] assumes that the average scene reflectance matches that of some other known color. Vrhel [37]assumes knowledge of the general covariance structure of the illuminant, given a small set of illuminants. Similarly, Freeman [9] assumes that the illumination and reflection in a scene follow known probability distributions. These methods are effective when the distribution of colors within the ....

M.J. Vrhel and H.J. Trussell, "Filter considerations in color correction" IEEE Transactions on Image Processing, 3:147-161, 1994.

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M. J. Vrhel and H. J. Trussell, "Filter considerations in color correction," IEEE Trans. Image Proc., vol. 3, no. 2, pp. 147--161, Mar. 1994.

.... applied to the combinatorial problem of selecting an appropriate set of filters for a scanner from given off theshelf candidate filters [204] A minimum mean squared error (MMSE) approach, which requires more statistical information than purely subspace based approaches, was introduced in [205], where numerical approaches for minimizing errors in uniform color spaces were also considered. In [206] noise was included in the analysis, and [207] 209] emphasized the reduction of perceived color errors in a hybrid device capable of measuring both reflective and emissive objects through ....

M. J. Vrhel and H. J. Trussell, "Filter considerations in color correction," IEEE Trans. Image Processing, vol. 3, pp. 147--161, Mar. 1994.

....in CIE XYZ space. Since the CIE XYZ space is known to be perceptually extremely nonuniform, a measure based on a uniform color space, such as the CIELAB space [1] 2] could offer significant advantages over these measures. Such a measure was implicit in the formulation used by Vrhel and Trussell [6] for the design of filters. The nonlinear nature of uniform color spaces, however, necessitates a considerable increase in computation. Recently, Wolski et al. 7] 8] proposed the use of global and local linearizations of CIELAB space to reduce the computational complexity while preserving the ....

M. J. Vrhel and H. J. Trussell, "Filter considerations in color correction," IEEE Trans. Image Processing, vol. 3, pp. 147--161, Mar. 1994.

No context found.

M.J. Vrhel and H.J. Trussell, "Filter considerations in color correction", IEEE Trans on Image Proc., vol. 3, No. 2, pp. 147-161, March 1994.

No context found.

M. J. Vrhel, H. J. Trussell, "Filter Considerations in Color Correction", IEEE Transactions on Image Processing, Vol 3, No. 2, pp. 147-161, Mar 1994

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Michael J. Vrhel and H. Joel Trussell, Filter Considerations in Color Correction, IEEE Transactions on Image Processing, 3, 147-161 (1994).

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