Byungki Cha

Sharpness preserving image enlargement by using self-decomposed codebook and Mahalanobis distance

We propose an image enlargement method preserving perceptual sharpness, which is achieved by augmenting a low resolution image with high-frequency components from a given image itself. The estimation of high-frequency image components is performed by a codebook built by a decomposition of the given image, i.e. a self-decomposed codebook. The rational that is exploited in this approach is the shape-invariant properties of edges across scales. As a distance measure for matching from the codebook, we employ the Mahalanobis distance which is a local distance measure incorporating pixel correlation. The effectiveness of the proposed method is verified by some image enlargement experiments. Consequently, the experimental results show that the performance of the proposed method is superior to other conventional image enlargement methods objectively and subjectively.

Super-Resolution via Matching from Self-Decomposed Codebook with Local Distance Measure Incorporating Pixel Correlation

We propose a method for constructing an image of high resolution by augmenting a low resolution image with high frequency components from a given image itself. The estimation of high frequency image components is performed by a codebook built by a decomposition of the given image, i.e. self-decomposed codebook. The rational that is exploited in this approach is the shape-invariant properties of edges across scale. As a distance measure for matching from the codebook, we employ a local distance measure incorporating pixel correlation. The effectiveness of the proposed method is verified by some image super-resolution experiments. Consequently, the experimental results show that the performance of the proposed method is superior to other typical image super-resolution methods objectively and subjectively.

3D animation watermarking using positioninterpolator

For real-time animation, keyframe animation that consists of translation, rotation, scaling interpolator nodes is used widely in 3D graphics. This paper presents 3D keyframe animation watermarking based on vertex coordinates in CoordIndex node and keyvalues in PositionInterpolator node for VRML animation. Experimental results verify that the proposed algorithm has the robustness against geometrical attacks and timeline attacks as well as the invisibility.

A Color Quantization Based on Vector Error Diffusion and Particle Swarm Optimization Considering Human Visibility

In this paper, we propose a new color quantization method for generation of the color-reduced images. The proposed method employs a vector error diffusion VED method and a particle swarm optimization PSO. VED method based on Floyd-Steinberg dithering is used for display of the color-reduced image. Furthermore, a color palette used in VED method is optimized by PSO. PSO generates the effective color palette with evaluating a human visibility of the color-reduced image on the display. The validity and the effectiveness of the proposed method are confirmed by some experiments.

Hierarchal Predefined Codebook for High-Frequency Component Augmentation Image Enlargement

A high-quality image enlargement is achieved by an estimation of high-frequency component. A codebook based method, which consists of a relationship of high and low-frequency image components, is known as one of the high-quality image enlargement. However, it takes too much calculation time, and is not appropriate for a real-time application such as a moving image enlargement. In this paper, we propose a hierarchal predefined codebook which achieves both of a fast calculation and a high-quality image enlargement. First, we define 1,904 code words generated from fundamental edge patterns. Then, the vector quantization is applied to the generated code words, and dividing 1,904 code words into 225 clusters. Finally, we obtain the hierarchal predefined codebook based on the divided code words. Experimental results show that the proposed method achieved both of a fast calculation and a high-quality image enlargement.

Fast Minimum-Spanning-Tree-like Based Image Segmentation

We propose a fast segmentation technique for segmenting natural images into meaningful regions based on a minimum spanning tree (MST) principle. The main idea of the technique comes from the redundancy of MST based image segmentation process. We compared the performance of the proposed technique with the performance of depth first search (DFS) and of the traditional MST. Finally, the simple split and merge method based on the proposed technique is proposed with some natural images of the Berkeley segmentation dataset and compared with our results with humans handi-labeled segmentation results.