An image processing method is proposed to realize polarizer-free imaging of liquid crystal lens. Images I(l) and I(nl) are captured sequentially in the lens and non-lens states of the LC lens, respectively, and are used to generate a final high contrast image. The proposal is tested by experiments. Clear and well focused images are obtained, even though no polarizer is employed in the imaging system.
Organic light emitting diode (OLED) displays use red, green, and blue primaries with a higher saturation level to produce larger color gamuts than conventional liquid crystal displays (LCD). No past study, however, experimentally investigated how such a difference between these two display types causes color mismatch and observer metamerism using the most widely used color matching functions (CMFs)—the CIE 1931 2° CMFs—for color calibration and specification. In this study, 50 human observers performed color matching tasks for six color stimuli with a field-of-view of 4.77° between four test displays (i.e., one LCD and three OLED) and a reference OLED display. The color gamuts of the LCD and OLED displays were similar to the sRGB and P3 standard color gamuts. It was found the CIE 1931 2° CMFs cannot accurately characterize the color matches between the LCD and OLED displays, with different chromaticities required to produce matched color appearance. Particularly, when the stimuli had matched color appearance, the chromaticities of the stimuli produced by the LCD display were all shifted towards the -u’+v’ direction in the CIE 1976 u’v’ chromaticity diagram in comparison to those produced by the OLED display. This suggested that using the CIE 1931 2° CMFs for display calibration would cause the colors shown on OLED displays to have a yellow-green tint if those on LCD displays appear neutral. In addition, a larger degree of observer metamerism was found between the LCD and OLED displays, while little differences, in terms of color mismatch and observer metamerism, were found between the OLED displays. The CIE 2006 2° CMFs were found to have better performance than the CIE 1931 2°, 1964 10°, and 2006 10° CMFs, which could be partially due to the size of the stimulus used in the experiment.
Local invariant features have been successfully used in image matching to cope with viewpoint change, partial occlusion, and clutters. However, when these factors become too strong, there will be a lot of mismatches due to the limited repeatability and discriminative power of features. In this paper, we present an efficient approach to remove the false matches and propagate the correct ones for the affine invariant features which represent the state-of-the-art local invariance. First, a pair-wise affine consistency measure is proposed to evaluate the consensus of the matches of affine invariant regions. The measure takes into account both the keypoint location and the region shape, size, and orientation. Based on this measure, a geometric filter is then presented which can efficiently remove the outliers from the initial matches, and is robust to severe clutters and non-rigid deformation. To increase the correct matches, we propose a global match refinement and propagation method that simultaneously finds a optimal group of local affine transforms to relate the features in two images. The global method is capable of producing a quasi-dense set of matches even for the weakly textured surfaces that suffer strong rigid transformation or non-rigid deformation. The strong capability of the proposed method in dealing with significant viewpoint change, non-rigid deformation, and low-texture objects is demonstrated in experiments of image matching, object recognition, and image based rendering.
In this paper, we present an external calibration technique for typical multi-camera system. The technique is very handy in practice using a simple planar pattern. Based on homography, an efficient pair-wise estimation method is proposed to recover the rigid rotation and translation between neighboring cameras. By registering all these partial calibrated structures, complete calibration of the multi-camera system is accomplished. Experiments with both simulated and real data show that accurate and stable calibration results can be achieved by the proposed method.
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