Recently, holographic display and computer-generated holograms calculated from real existing objects have been more actively investigated to support holographic video applications. In this paper, we proposed a method of generating 360-degree color holograms of real 3D objects in an efficient manner. 360-degree 3D images are generated using the actual 3D image acquisition system consisting of a depth camera and a turntable and intermediate view generation. Then, 360-degree color holograms are calculated using a viewing-window-based computer-generated hologram. We confirmed that floating 3D objects are faithfully reconstructed around a 360-degree direction using our 360-degree tabletop color holographic display.

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In order to reconstruct a 3D model in video sequences

The primary goal of image color correction is to minimize color confusion for those people who experience deficiencies in their ability to distinguish certain colors. When the colors in a particular image are converted so as to make them perceivable to color vision deficient people, most of the existing methods correct all the colors of the image instead of only the specific colors that are confused. When ordinary people view the images converted using such techniques, they experience a significant difference in perception. To solve this problem, this study investigates the color perception of color vision deficient people through analysis of confused color regions in images and proposes a new method that corrects the minimum number of color regions into optimal colors. For this purpose, the proposed method builds a confusion line database for colors confused by color vision deficient people using the CIEDE2000 color-difference formula and Brettel's method for simulation of color vision deficiency in the offline stage. In the online processing stage, regions are divided through the region growing technique, and the colors in the divided images are compared. When there exist confused colors by color vision deficient people, a method for finding the optimal color is proposed through the confusion line database. Furthermore, this study developed an optimization index to propose a method of finding such optimal colors and validated them through various tests. The excellence of the color correction results of this study was demonstrated based on an objective index as well as on participants' subjective visual perception through comparative experiments with other existing studies. INDEX TERMS Color correction, color vision deficiency, confusion line, image processing, region growing.

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