Min Cheol Hwang

Vector quantizer based block truncation coding for color image compression in LCD overdrive

The overdrive technique has been popularly used to alleviate the motion blur on liquid-crystal display (LCD) by shortening the response time of the liquid crystal. However, this technique requires a large frame buffer to store the previous frame as a reference. In this paper, we propose a novel block truncation coding based on the vector quantizer for the color image compression in LCD overdrive. Due to the constant output bit-rate and the low computational complexity, the proposed method is suitable for the hardware implementation in LCD overdrive. Experimental results show that the proposed method achieves higher compression ratio as well as better visual quality as compared with the conventional methods.

Hybrid Temporal Error Concealment Methods for Block-Based Compressed Video Transmission

Boundary matching algorithm (BMA) and decoder motion vector estimation (DMVE) are two well-known temporal error concealment methods using the matching-based approach. In these two methods, the motion vector of each missing block is estimated by choosing one among candidate motion vectors which minimizes a sum of absolute differences (SAD) between boundary pixels of the corrupted macroblock. In general, the performance of DMVE is better than that of BMA. However, depending on the location or pattern of the corrupted block, BMA produces higher visual quality than DMVE. In this paper, we propose two types of hybrid error concealment methods; switching method and blending method. The switching method chooses one of two results obtained by BMA and DMVE based on the normalized SAD values. In the blending method, the weighted sum of the results concealed by the aforementioned two methods is utilized to improve the performance of error concealment. In order to reduce blocking artifacts further, the modified overlapped-block motion compensation is adaptively applied to the concealed blocks. Simulation results show that the proposed methods outperform other techniques in terms of subjective visual quality as well as PSNR performance.

Person identification system for future digital tv with intelligence

Intelligent digital TV (iDTV) is a future digital TV with intelligence which can automatically provide user-personalized services for each audience. For the user-personalized services, the iDTV should recognize audiences in real-time. In this paper, we define a novel structure of the iDTV and propose a real-time person identification system in the iDTV that analyzes captured images and recognizes audiences. The proposed system consists of three processing units: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach, and face recognition using support vector machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of 90% or higher at the speed of 15~20 fps, which is suitable for the iDTV

Frame Error Concealment Technique Using Adaptive Inter-Mode Estimation for H.264/AVC

Since H.264/AVC achieves a high compression ratio by reducing spatio-temporal redundancy in video sequences, the payload of a single packet can often contain a whole frame encoded by H.264/AVC. Therefore, the loss of a single packet does not only cause the loss of a whole frame, but also produce error propagation. In this paper, we propose a novel whole frame error concealment method using adaptive inter-mode estimation for H.264/AVC. Experimental results show that the proposed method exhibits the better PSNR performance as compared with conventional methods.

Improved Fading Scheme for Spatio-Temporal Error Concealment in Video Transmission

Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixel-wisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.

Improved block truncation coding for color image compression in LCD overdrive

The overdrive techniques have been widely used to reduce motion blur on liquid-crystal displays (LCD). However, these techniques require a large size of the frame buffer to shorten the response time of the liquid crystal. In this paper, we propose an improved block truncation coding (BTC) that can significantly reduce the memory used for the overdrive. Experimental results show that the proposed algorithm improves the compression ratio by a factor of two while maintaining the edge preservation characteristics as compared with the conventional BTC algorithm.

Real-Time Person Identification System for Intelligent Digital TV

Intelligent digital TV (iDTV) is an enhanced digital TV that can automatically provide user-personalized services for each audience. For the user-personalized services, the iDTV should recognize audiences in real-time. Thus, in this paper, we define a novel structure of the iDTV and propose a real-time person identification system embedded in the iDTV. The proposed system consists of three phases: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach with Haar-like features, and face recognition using support vector machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of above 90% at the speed of 15~20 fps, which is suitable for applying to the iDTV.

Video transcoding to support playback at a random location for scalable video coding

In many applications including Internet video broadcast and interactive TV, video streams are transmitted over various networks. In order to fulfil the requirement of the users who want to watch a part of the video stream, start playback at a random location, and jump to another location, the service provider has to implement the random access functionality. In addition, when the video stream is transmitted over error-prone networks like wireless LAN, the random access point can be used as a recovery point which enables the user device to refresh the decoding process corrupted by the transmission error. In this paper, we propose a simple transcoding algorithm inserting the random access point in the pre-encoded video stream. The multimedia server adopting the proposed transcoding algorithm can support the error-resilient transmission as well as the playback at random location. Experimental results show that the proposed method can gain significant reduction in the complexity without introducing degradation on visual quality.

Inverse Motion Compensation for DCT Block with Unrestricted Motion Vectors

Existing methods for inverse motion compensation (IMC) in the DCT domain have not considered the unrestricted motion vector (UMV). In the existing methods, IMC is performed to deal with the UMV in the spatial domain after the inverse DCT (IDCT). We propose an IMC method which can deal with the UMV directly in the DCT domain without the use of the IDCT/DCT required by the existing methods. The computational complexity of the proposed method can be reduced by about half of that of the brute-force method operating in the spatial domain. Experimental results show that the proposed method can efficiently reduce the processing time with similar visual quality.

Efficient Compression Scheme For Time Codes in Karoale

In Karaoke, the displaying of lyrics synchronized with music is the most crucial feature. To synchronize lyrics with music, the time code has been widely used. In general, a huge amount of time codes for one song is required. Thus, the uncompressed time code is a big burden on the mobile device. In this paper, we propose a novel method to compress the time code for Karaoke further. The proposed method uses the correlation between neighboring time codes. In addition, an effective coding method is designed to compress the data of the time code. Experimental results show that the proposed method significantly reduces an amount of data of time codes and is easily applied to other composite contents with time code