Chae-Bong Sohn

Blocking artifact reduction in JPEG-coded images

We proposed the post-processing method to reduce the blocking artifact in low-bit-rate coded JPEG images, which is based on minimum block-boundary-discontinuity criterion. We analyzed the statistical property of block boundary pixel difference, classified all blocks into one of two types using OSLD (overlapped sub-laplacian distribution), and compensated the quantization error depending on the type of block, adaptively. Our postprocessing method can provide better visual quality as well as PSNR than any other method.

Fast motion estimation for HEVC with adaptive search range decision on CPU and GPU

In this paper, we propose a fast Motion Estimation (ME) algorithm with Adaptive Search Range (ASR) decision to further accelerate the Graphics Processing Units (GPU)-based ME for High Efficiency Video Coding (HEVC). The proposed approach adaptively decides search ranges on the Central Processing Unit (CPU) and transfers them to the GPU. Then, the GPU performs ME process in parallel. The proposed approach solves the dependency problem in the Motion Vector Predictor (MVP) derivation stage by using only temporal Motion Vectors (MVs). The proposed algorithm yields the total encoding time reduction of 40.3% with negligible Rate Distortion (RD) loss of 1.2%. In terms of ME, the GPU-based ME with ASR decision provides the time reduction of 54.7% and 1446.8× speed-up on average compared to the GPU-based ME without ASR decision and the full-search ME in the reference model, respectively.

EPITRANS: A Database that Integrates Epigenome and Transcriptome Data

Epigenetic modifications affect gene expression and thereby govern a wide range of biological processes such as differentiation, development and tumorigenesis. Recent initiatives to define genome-wide DNA methylation and histone modification profiles by microarray and sequencing methods have led to the construction of databases. These databases are repositories for international epigenetic consortiums or provide mining results from PubMed, but do not integrate the epigenetic information with gene expression changes. In order to overcome this limitation, we constructed EPITRANS, a novel database that visualizes the relationships between gene expression and epigenetic modifications. EPITRANS uses combined analysis of epigenetic modification and gene expression to search for cell function-related epigenetic and transcriptomic alterations (Freely available on the web at http://epitrans.org).

A novel video copy detection method based on statistical analysis

The careless illegally copied contents have been rising serious social problem as internet and multimedia technologies are developing. Therefore, effective and efficient copy detection techniques are required for content management and rights protection. In this paper, we propose a content-based hierarchical video copy detection method that estimates similarity using statistical characteristics between an original video and its spatial variations. We rank luminance average value of video that is robust to the special transformation, and choose similar video sequences named as candidate segments in huge amount of database to reduce processing time and complexity. Finally, we detect the copied video by using the hypothesis test of mean. As experiment result, proposed method has similar copy detection ratio accuracy to the reference method while our processing time and complexity are less than those of the reference since we can reduce the number of keyframes up to 50%. Also, the proposed method can efficiently detect spatial variations such as blur, contrast change, zoom in, and zoom out.

A Novel Video Copy Detection Method based on Statistical Analysis

The carelessly and illegally copied contents are raising serious social problem as internet and multimedia technologies are advancing. Therefore, development of video copy detection system must be settled without delay. In this paper, we propose the hierarchical video copy detection method that estimates similarity using statistical characteristics between original video and manipulated(transformed) copy video. We rank according to luminance value of video to be robust to spacial transformation, and choose similar videos categorized as candidate segments in huge amount of database to reduce processing time and complexity. The copy videos generally insert black area in the edge of the image, so we remove rig black area and decide copy or not by using statistical characteristics of original video and copied video with center part of frame that contains important information of video. Experiment results show that the proposed method has similar keyframe accuracy to reference method, but we use less memory to save feature information than reference`s, because the number of keyframes is less 61% than that of reference`s. Also, the proposed method detects if the video is copied or not efficiently despite expansive spatial transformations such as blurring, contrast change, zoom in, zoom out, aspect ratio change, and caption insertion.

An Efficient Thumbnail Extraction Method in H.264/AVC Bitstreams

Recently, as growing of high definition media services like HDTV and IPTV, fast moving picture manipulation techniques need to meet what those services require. Especially, a fast reduced-size image extracting method is required in the areas of video indexing and video summary Conventional DC image extracting methods, however, can`t be applied to H.264/AVC streams since a spatial domain prediction scheme is adopted in H.264/AVC intra mode. In this paper, we propose a theoretical method for extracting a thumbnail image from an H.264/AVC intra frame in the frequency domain. Furthermore, the proposed scheme can extract the thumbnail very fast since all operations are applied to transform coefficients directly, after a general equation for the thumbnail extraction in nine H.264/AVC intra prediction modes is introduced, an LUT(Look Up Table) for each mode is designed. Through the implementation and performance evaluation, while the subject quality difference between the output of our scheme and a conventional output is negligible, the former can extract the thumbnail faster then the latter by up to 63%.

Residual signal compression based on the blind signal decomposition for video coding

In this paper, a new residual signal compression method is proposed based on the blind signal decomposition for video coding. Blind signal decomposition is derived based on the fact that most of the natural signals in the real world could be decomposed into their basis signals and their weight values used in the composition process. In the proposed video coding system, composite data generated by adding two or more blocks are coded. Then the proposed decoder parses the coded bitstream and reconstructs the composite residual. The reconstructed composite residual is decomposed into the original residual blocks based on the blind signal decomposition. In the proposed system, the blind source separation is selectively used, depending on the performance of source separation. It is found that we can achieve approximately 2 ∼ 3dB gain by embedding our algorithm into an MPEG-4 baseline encoder.

Spatial interpolation algorithm for consecutive block error using the just-noticeable-distortion method

This paper presents a new error concealment algorithm based on edge-oriented spatial interpolation as well as the JND (Just-Noticeable-Distortion) function to select valid edge information in adjacent blocks. Several conventional algorithms suffer from computational complexity or inaccurate recovery at missing blocks having strong edgeness. In order to alleviate these drawbacks, the proposed algorithm estimates a dominant direction to interpolate the missing pixel values. At this step, automatic thresholding method based on the JND function is proposed to determine a valid direction. Then, a lost block is recovered by weighted linear interpolation along the dominant vector. Finally, the median filter is applied to recover pixels that are not located on the line with the estimated dominant direction. Simulation results show that the proposed algorithm improves the PSNR of the recovered image approximately 2.5dB better than Hsias and can significantly reduce computational complexity with keeping subjective quality as good as the RIBMAP method.

Action Game with Automatic Background Music Generation Using Genetic Algorithm

The genetic algorithm (GA), one of the artificial intelligence (AI), is developed based on Darwins theory of evolution, i.e., the mating of randomly selected objects. If more optimal solution is generated, then it is better to repeat the process of setting the optimum value. In this paper, the method of background music using the genetic algorithm is exploited when the computer game is executed each time. As a result, it has created several music that can be used in the actual game, and it could be confirmed that the other music that is created is different music when performed each time.

A fast luminance intra 4×4 prediction mode decision method by statistical analysis of residual data in H.264/AVC

In H.264/AVC, intra prediction mode decision using rate distortion optimization (RDO) improves coding efficiency but requires high computational complexity. There is a close correlation between the best mode by RDO and the energy of the residual data. In this paper we propose a fast intra 4×4 block prediction mode decision method by statistical analysis of the relationship between RDO and residual data. The proposed method reduces the intra 4×4 block encoding time by about 57.4%, while decreasing coding gain by about 0.29%.