Kyeong-man Kim

Gamut mapping using variable anchor points

Recently, a variety of imaging devices are being used to represent electronic color images the reproduced color, however, is different from the original color because of the difference of producible colors on the devices. The range of producible colors offered by a device is referred to as its gamut. In his paper, a gamut-mapping algorithm (GMA) is proposed that can maintain device-independent color. Categorized as a parametric GMA, this algorithm utilizes variable anchor points to both reduce a sudden color change on the gamut boundary of the printer and to maintain a uniform color change during the mapping process. Accordingly, the proposed algorithm can reproduce high quality images with low-cost color devices.

New video segmentation algorithm using a combined segmentation measure for content-based coding

A new video segmentation algorithm using a combined seg- mentation measure for content-based coding is presented. The com- bined segmentation measure is a weighted sum of intensity, motion, and a change segmentation measure. The change segmentation measure is defined from a change image, which is obtained from the proposed change detector. The proposed change detector performs morphological erosion filtering to eliminate many inaccurate components, included in the resulting image obtained from a conventional change detector. Since the change segmentation measure is defined as an absolute change value difference between a pixel and its neighboring region, it can be an efficient segmentation measure for the accurate segmentation of neigh- boring moving objects and static background regions. Therefore, the pro- posed combined segmentation measure can determine exact bound- aries even though the estimated motion vectors around the boundaries of moving objects and static background regions are inaccurate and the intensities around the boundaries are similar. From the experimental re- sults for a video segmentation, since the combined segmentation mea- sure can accurately segment the boundaries between moving objects and static background regions, the motion compensated images pro- duced by the proposed segmentation algorithm show improved image quality compared to the conventional segmentation.