Sungjei Kim

A directional deblocking filter based on intra prediction for H.264/AVC

Although the adaptive deblocking filter of H.264/AVC efficiently reduces blocking artifacts for most images, it is limited in removing the blocking artifacts of the directional edge on the block boundaries. In order to solve this problem, we propose a directional deblocking filter based on intra prediction direction. The proposed algorithm performs directional filtering according to the direction of the intra prediction mode in order to correctly find the block edge while avoiding computational burden. Experimental results show that the proposed algorithm provides subjective improvements at the directional edge and PSNR gain of up to 0.13dB.

Direction-adaptive context modeling for sign coding in embedded wavelet image coder

The conventional embedded wavelet image coder exploiting the adjacent neighbors is limited to efficiently compress the sign coefficients, since the wavelet coefficients are highly correlated along the dominant image features, such as edges or contours. To solve the problem, in this paper, we propose the direction-adaptive sign context modeling by adaptively exploiting the neighbors suitable to the dominant image features. Experimental results show that the sign coding based on the proposed context modeling reduces the sign bits up to 5.5% compared to the conventional sign coding method.

An enhanced touch event processing on Android

The evolution of Android smartphone has increased the importance of touchscreen capabilities as user interaction as well as user input method. However, due to the limitation of Android architecture, every touch event may not create its corresponding display update all the times. To overcome this limitation, this paper proposes a novel technique of Touch Event Handling Block (TEHB) with capability of virtual touch event generation and low pass filters. TEHB is implemented on Android 2.2 and its performance simulations show that TEHB can achieve more performance gain than conventional triggering method.

Advanced intra prediction based on optimal linear predictors for weakly-predicted subspace

The performance of intra coding is important in many broadcasting and professional applications, because repeated insertion of intra frames usually requires a large portion of video data. In order to improve such intra coding performance, this paper proposes an advanced intra prediction scheme, systematically increasing prediction precision via optimal linear predictors for weakly-predicted subspace. Experimental results show that the proposed scheme outperforms the conventional and the recent best intra prediction methods by up to 11.41% and 9.08% of bitrate reduction, respectively.

An efficient skip mode competition scheme based on vector clustering and object boundary detection

In video coding, a portion of skipped macroblocks is highly effective to the coding performance, especially, at low bitrates since, for a skip mode, no additional coding parameters are transmitted except mode index itself. To increase the skip mode occurrence, in this paper, we propose an efficient skip mode competition scheme based on vector clustering of multiple predictive motion vectors (PMV) and boundary detection of moving objects. The proposed scheme selects the best PMV of skip mode optimally among representative PMV candidates which are obtained after the clustering process and switches a more appropriate competition scheme adaptively according to object boundary conditions. Experimental results show that the proposed scheme reduces average 4.31% in BDRATE compared to the KTA 2.6 software.