• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.12-15
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• 1996

The purpose of image sequence coding is to reduce the spatio-temporal redundancies. The transform coding such as DCT is used for the spatial redundancies. In this paper, the optical flow method is applied to solve the problem of temporal redundancies. So far, pixel intensity conservation has been used to solve the optical flow. We used the neighborhood information as well as pixel intensity conservation. And we compared the merits and demerits of the conventional method and the proposed method in this paper.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1350-1352
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• 1996

The purpose of image sequence coding is to reduce the spatio-temporal redundancies. For the spatial redundancies, we can use the transform coding such as DCT. In this paper, the optical flow method is applied to solve the problem of temporal redundancies. There are several estimation methods like block matching method and pel-recursive method. Block matching method is easy for a hardware implementation because of the computational simplicity. So, it is now used as the estimation method in MPEG-l, MPEG-2, and H.261. We compared the merits and demerits of the optical flow method and the block matching method in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.360-373
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• 2017

This paper presents a novel digital video steganalysis scheme against the spatial domain video steganography technology based on a spatial temporal detector (ST_D) that considers both spatial and temporal redundancies of the video sequences simultaneously. Three descriptors are constructed on XY, XT and YT planes respectively to depict the spatial and temporal relationship between the current pixel and its adjacent pixels. Considering the impact of local motion intensity and texture complexity on the histogram distribution of three descriptors, each frame is segmented into non-overlapped blocks that are $8{\times}8$ in size for motion and texture analysis. Subsequently, texture and motion factors are introduced to provide reasonable weights for histograms of the three descriptors of each block. After further weighted modulation, the statistics of the histograms of the three descriptors are concatenated into a single value to build the global description of ST_D. The experimental results demonstrate the great advantage of our features relative to those of the rich model (RM), the subtractive pixel adjacency model (SPAM) and subtractive prediction error adjacency matrix (SPEAM), especially for compressed videos, which constitute most Internet videos.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.787-797
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• 2008

In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.167-175
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• 2000

Compressed bitstreams generated by an MPEG-2 video encoder (or digital TV picture transmission are quite sensitive to channel errors. Due to the coding structure of the MPEG-2 video compression algorithm, a single bit error can affect not only the current Picture frame but also succeeding frames. Error concealment algorithms attempt to repair damaged portions of the picture by exploiting spatial and temporal redundancies in the correctly received and reconstructed video frames. In this paper, we analyze the effect of channel errors in MPEG-2 video bitstreams and estimate lost motion vectors by exploiting temporal redundancies in the video frames. Motion vectors can be estimated from the vertically adjacent extended region of lost macroblocks. Finally, we conceal the damaged macroblocks by compensating the displacement with the estimated motion vectors. Simulation results demonstrate that both the weighted sum algorithm and the extension matching algorithm achieve good performance in terms of PSNR values as well as subjective image quality.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.65-74
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• 2006

The MPEG-2 video compressed bitstream is very sensitive to transmission errors due to the complex coding structure of the MPEG-2 video coding standard. If one packet is lost or received with errors, not only the current frame will be corrupted, but also errors will propagate to succeeding frames within a group of pictures. Therefore, we employ various error resilient coding/decoding techniques to protect and reduce the transmission error effects. Error concealment technique is one of them. Error concealment technique exploits spatial and temporal redundancies of the correctly received video data to conceal the corrupted video data. Motion vector recovery and compensation with the estimated motion vector is good approach to conceal the corrupted data. In this paper, we propose various error concealment algorithms based on motion vector recovery, and compare their performance to those of conventional error concealment methods.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.303-310
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• 2007

Compressed video bitstreams are intended for real-time transmission over communication networks. Because video compression algorithms eliminate the temporal, spatial, and statistical redundancies, the coded video bitstreams are very sensitive to transmission errors. We propose an error resilient video coding technique to limit the effect of error propagation in low bit-rate video coding. The success of error resilient coding techniques relies on how accurately the transmission errors can be detected. To detect the transmission error, we propose a very simple error detection technique based on data hiding Next, we conceal the corrupted MB data using intra MB refresh and motion compensation with the estimated motion vector and compare the simulation results. This method will be useful in video communication in error Prone environment such as WCDMA networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.653-664
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• 2010

Generally existing video codec employs entropy coding to deal with residual signals with considering temporal and spatial properties. Scalable Video Coding(SVC) which is extension of H.264/AVC has three technical concepts for removing redundancies between inter-layers. In spite of using novel prediction method between inter-layers in SVC, it is still using same entropy coding method to residual signals. According to the studies, the residual obtained by inter-layer prediction technique has different features of residual signal acquired by spatial or temporal prediction technique. In this paper, we propose an efficient entropy coding method which codes the residual signal obtained by inter-layer prediction with regarding its features adequately. We re-designed the Coded Block Pattern(CBP) table suitably for inter-layer texture prediction. The experiments show that the proposed method can further reduce the BD-Bitrate up to average 2.20% in 4CIF and 1.14% in CIF resolution compared to the existing JSVM 9.18.