Beomsu Kim

Hole Filling Algorithm Using Spatial-Temporal Background Depth Map for View Synthesis in Free View Point Television

This paper presents a new hole filling algorithm based on background modeling and texture synthesis. Depth information of hole areas is computed by using a local background estimation method. In order to exploit the correlation between frames in temporal domain, a background modeling method is used to extract reliable background reference scenes. The holes are then filled by combining the temporal background information and the estimated depth information. A modified exemplar-based inpainting method is used to fill remaining hole pixels. Experimental results demonstrate the capability of the proposed algorithm.

Video Stabilization Based on Smoothing Filter of Undesirable Motion

Please This paper presents method of video stabilization based on detection and adaptive motion smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.

Image enhancement and post-processing for low-resolution compressed video

This research paper recommends the PSF (Point Spread Function) prediction technique based on the POCS (Projection On to Convex Set) and regularization to acquire low resolution images. As the environment for the production of YouTube videos (one of the contents on the Internet) becomes widespread, resolution reduction and image distortion occurs, failing to satisfy users who desire high quality images. Accordingly, this research neutralizes the coding artifact through POCS and regularization processes by: 1) factoring the local characteristics of the image when it comes to the noise that results during the DCT and quantization process; and 2) removing the blocking and ring phenomena which are problems with existing video compression. Moreover, this research predicts the PSF in order to obtain low resolution images using the above--mentioned methods in order to suggest a method for minimizing the errors found among the predicted interpolation pixels. Low-resolution image quality obtained through the experiment demonstrates that significant enhancement was made on the visual level compared to the original image.

MRF-based adaptive detection approach: a framework for restoring image degraded by Gaussian noise

This paper proposes a spatially adaptive noise-detection and removal algorithm. The noise component is estimated with local statistics from an observed degraded image. In addition, the first order MRF is effectively used to improve the noise detection performance prior to apply an adaptive low-pass filter having a variable filter window. Experimental results demonstrate the capability of the proposed algorithm.