Earticle

In this paper, we propose an efficient algorithm for encoding of MPEG-4 simple profile. In the proposed algorithm, I frame encoding adopts all phase biorthogonal transform (APBT); for P frames, each frame puts the reconstructed frame of previous coded one as the reference frame to perform motion estimation (ME) and motion compensation (MC), and then the encoding of residual frame uses discrete cosine transform (DCT). While the proposed algorithm applying on MPEG-4, the objective effect and visual quality of reconstructed video sequence are approximate to the one based on DCT at the same bit rates. But the advantage is that the APBT transform coefficients can be quantized uniformly. Therefore the computing time is shorted and hardware implementation becomes easier. The proposed algorithm uses low computational complexity to make it applicable to encoding of MPEG-4 simple profile.

오늘날 컴퓨터 네트워크 인프라 구축이 일반화되고 인터넷 사용자의 수가 증가하는 가운데 망에는 대용량의 트래픽이 흐르고 있다. 네트워크 트래픽은 2014년에 월간 47 엑사바이트(Exabyte), 2015년 월간 62 엑사바이트로 엄청 난 증가를 보인다. 인터넷 트래픽 중에서 동영상 트래픽의 비중은 전체 60%를 차지하여 인터넷 트래픽 상승의 견인차 역할을 수행하고 있다. 엄청난 인터넷 트래픽의 성장에 비해서 네트워크 인프라는 이를 지원하기 턱없이 부족하여 모 바일 네트워크에서 음성통화의 품질저하라는 극단적인 부작용이 나타나고 있다. 미래에 예상되는 잠재적인 위험을 사전 에 방지하기 위해 SURF 특징과 블록 모양을 이용한 동영상 압축 방법을 제안한다. 제안한 방법은 기존의 방법보다 좋은 성능을 보이는 것을 확인하였다.

Today, computer network infrastructure is commonplace and internet user increase. Transmission bandwidth for network traffic is increasing. The data amount of 2014 and 2015 year measured 47 and 62 exabyte, it shows a tremendous increase. Video traffic occupy 60 percent among internet traffic. Enormous growth of Internet traffic than the network infrastructure is not enough to support them, so mobile network occur side-effects such as fall of voice communication. In this paper, we proposed the video compression method using SURF feature and block shaping in order to avoid potential damage. Our proposed method can provide enough performance than previous method.

With the increasing threats on multimedia information sharing, degradation of security is one of the most important concerns. Visual Cryptography is an emerging field for improving the security level by encoding the secret video using encryption scheme and performs computational free decoding process. The secret sharing through visual cryptographic techniques for multiple stack users is not sufficient in providing high percentage result on video sharing domain. Video sharing did not develop source key properties for individual frames and as a result the quality estimation strategy on video frame was not achieved. Moreover, the target rate constraint for video quality under the encryption-decryption was not achieved. This encryption-decryption target key rate declines on arranging multiple sequences of frames from multiple stack users. To improve the quality of visual secret video sharing scheme, a Discrete Cosine Transform Chaos Cryptographic (DCTCC) mechanism is proposed in this paper. The main objective of DCTCC is to enhance the security level of different level video frame using the encryption key properties. Initially, sender takes the video of differing frame length and compresses the video on image using the Discrete Cosine Transformer. The Discrete Cosine Transformer based visual secret sharing of video in the image takes the luminance values and provides high lossless compression. Second, the embedded video frame is encrypted to perform the secret sharing (i.e., visual cryptographic) using the chaos method. The Chaos method uses the enhanced RSA key properties to improve the video quality estimation strategy. Chaos method in DCTCC works effectively with non-linear dynamic set of video frames from users and also with the discrete time dynamical video cryptographic system. On the decryption side, the chaos method is applied in the reverse procedural order to fetch the video quality of video frames from original image. Experiment is conducted on factors such as mean square error rate, and secret video sharing efficacy level and encryption time.

This paper presents a hybrid content-based video coding scheme that encodes arbitrary shaped objects instead of blocks of images. The scheme achieves efficient compression for low bit-rate applications by separating moving objects from stationary background and transmitting the shape, motion and residuals for each segmented object. Furthermore, a new content-based object segmentation algorithm is proposed in the scheme, which does not assume any prior modeling of the objects being segmented. The algorithm is based on a threshold function that calculates block histograms and takes image noise into account. The experimental results show that the scheme proposed outperforms the classical object-based coding methods in terms of PSNR or the average number of bits required for coding a single frame.

The vertical or horizontal edges don’t dominate in some frames of video sequence, so the conventional discrete cosine transform (DCT) may not be the best choice for those frames. Directional DCT framework behaves better than conventional DCT in coding performance for images where directional edges dominate. In addition, the all phase biorthogonal transform (APBT), which is used in image compression instead of DCT, can also help to improve the performance of compression. In the light of directional DCT and APBT, directional APBT (D- APBT) is proposed and applied to H.263 video coding. Experimental results show that this framework can indeed improve the coding performance remarkably.

As the international video coding standard, MPEG-2 has been widely used in today’s digital video applications. However, its quantization operation is complex. To simplify this operation, we propose a new algorithm for the intra frame transform-coding in this paper, instead of the conventional algorithm that using discrete cosine transform (DCT). This new algorithm is based on the all phase biorthogonal transform (APBT) theory, which has three kinds of forms in accordance with different transform matrices, referred to as the all phase Walsh biorthogonal transform (APWBT), the all phase discrete cosine biorthogonal transform (APDCBT), and the all phase inverse discrete cosine biorthogonal transform (APIDCBT). Compared with the conventional DCT, APBT reduces the inter-pixel redundancy and the computational complexity using the uniform quantization for the intra frames transform-coding. Experimental results show that the peak signal to noise ratio (PSNR) of the proposed algorithm performs close to the DCT for the tested frames, and there is no difference in visual quality.

Recently, computer network infrastructure is commonplace and internet user increase. Transmission bandwidth for network traffic is increasing and the type is varied such as real-time video. Video traffic occupies much volume among Internet backbone traffic, transmission bandwidth and quality of service (QoS) of other network application such as web, email cannot be guaranteed. In this paper, we propose a block information-based video compression method. The proposed method uses scenes, memorial/non-memorial blocks, and SIFT parameters as compression structure, compression units, and a compression method, respectively. This electronic document is a “live” template. Experimental results showed that the proposed method has better performance than H.264/AVC main profile in objective quality, compression ratio.

To improve and enhance the estimation speed and accuracy of motion estimation, this paper proposes a fast diamond search algorithm with improved search strategy; researches motion estimation algorithm by using pattern block matching; analyzes and set up fast searching algorithm model based on the fast convergence characteristics of three step search, the central distribution characteristics of new three step search and the approximate global optimal characteristics of diamond search; use the coarse positioning and fortified halfway stop technologies to establish improved diamond search algorithm; gives the method of reducing the number of search bits. Through experiment and analysis, the results show that the improved diamond search algorithm can effectively reduce the matching points

In surveillance systems, the storage requirements for video archival are a major concern because of recording of videos continuously for long periods of time, resulting in large amounts of data. Therefore, it is essential to apply efficient compression techniques for compressing surveillance video. The techniques used for the general video compression may not be the efficient technique for the compression of surveillance video because of the use of static camera as compared to moving camera in general purpose videos. Generally surveillance video consist of multiple objects, smaller in size as compared to the background and they have frequents occlusion with each other. In this paper a new object based motion estimation and compensation technique for surveillance video compression is proposed. Background differencing and summing technique (BDST) is used for the segmentation of the moving objects. This technique not only identifies moving object but also the maximum distance moved by the object in given group of frames. A bonding box is created based on the movement of the object in order to segment the moving objects. For exploiting the temporal redundancy, the motion estimation and compensation is carried out for the bonding box region only. The multiresolution property of discrete wavelet transform is used for the motion estimation and compensation. Experimental results show that the approach achieves high compression ratios compared to MPEG-2 compression.

다시점 비디오는 하나의 장면을 여러 대의 카메라를 이용하여 여러 시점에서 촬영한 것이다. 따라서 사용자의 요구에 의해서 원하는 시점의 비디오를 제공할 수 있는 장점을 갖는다. 본 논문에서는 보다 향상된 기법을 활용하여 계층적 깊이 영상 구조 표현의 압축 성능을 향상시켰다. 계층적 깊이 영상을 H.264 기술로 부호화시켜 압축된 데이터 크기를 확인하고, 복원된 각 영상의 품질 성능을 알아보았다. H.264/AVC 기술은 쉽게 비디오와 관련된 콘텐트에 대한 H.264 기술로 확장될 수 있다. 그래서 깊이 정보를 포함하는 다시점 영상을 효과적으로 압축할 수 있는 계층적 깊이 영상 구조라는 새로운 콘텐트에 적용하는 방법을 제안하였다. 다시점 비디오 영상의 막대한 데이터 양이 감소되며, 고품 질의 영상을 제공되고, 에러 복원 기능이 강화하는 장점이 있는 것을 보여주었다.

The multi-view video is a collection of multiple videos capturing the same scene at different viewpoints. Thus, there is an advantage of providing for user oriented view pointed video. This paper is suggested that the compression performance of layered depth image structure expression has improved by using more improved method. We confirm the data size of layer depth image by encoding H.264 technology and the each performances of reconstructed images. The H.264/AVC technology has easily extended for H.264 technology of video contents. In this paper, we suggested that layered depth structure can be applied for an efficient new image contents. We show that the huge data size of multi-view video image is decreased, and the higher performance of image is provided, and there is an advantage of for stressing error restoring.

In this paper, we propose the novel methodology to improve the rate-distortion characteristics by the difference of the quantized DCT coefficients using two different quantized parameters in HEVC. Under the special condition of the quantization property in HEVC, we evaluate the binary difference of the quantized DCT coefficients derived from two different quantized parameters and compressed it with simple CABAC algorithm based on the characteristics of the binary difference. The experimental result shows that the proposed algorithm improves the compression performance of the rate-distortion property in comparison to the conventional HEVC compression method.

For efficient transmission of 3DTV video signals, it is necessary to eliminate the inherent redundancy between the stereo image pairs. Though disparity estimation provides a powerful tool for eliminating the redundancy, it is very time consuming. This paper presents a novel disparity estimation scheme based on the human visual property. The disparity vectors of image blocks spatially adjacent to the current block are used as initial guesses fur the disparity vector of the current block. In addition, mixed-resolution coding is applied to reduce the computational complexity of disparity estimation. Through computer simulations on a stereoscopic sequence we show that the proposed method gives rise .to visually pleasing results with much reduced computational complexity.

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

An efficient algorithm to compress high dynamic range (HDR) videos is proposed in this work. We separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence. Then, we encode those two sequences using the standard H.264/AVC codec. During the encoding, we allocate a limited amount of bit budget to the LDR sequence and the ratio sequence adaptively to maximize the qualities of both the LDR and HDR sequences. While a conventional LDR decoder uses only the LDR stream, an HDR decoder can reconstruct the HDR video using the LDR stream and the ratio stream. Simulation results demonstrate that the proposed algorithm provides higher performance than the conventional methods.

Motion estimation is a core part of most video compression systems since it directly affects the output video quality and the encoding time. The full search (FS) technique gives the highest visual quality but has the problem of a significant computational load. To solve this problem, we present in this paper a modified median (MMED) operation and advanced search strategies for fast motion estimation. The proposed MMED operation includes a temporally co-located motion vector (MV) to select an appropriate initial candidate. Moreover, we introduce a search procedure that reduces the number of thresholds and simplifies the early termination conditions for the determination of a final MV. The experimental results show that the proposed approach achieves substantial speedup compared with the conventional methods including the motion vector field adaptive search technique (MVFAST) and predictive MVFAST (PMVFAST). The proposed algorithm also improves the PSNR values by increasing the correlation between the MVs, compared with the FS method.

In order to reduce the size of frame memory or bus bandwidth, frame memory compression (FMC) recompresses reconstructed or reference frames of video codecs. This paper proposes a novel FMC design based on discrete wavelet transform (DWT) - set partitioning in hierarchical trees (SPIHT), which supports fine-scalable throughput and is area-efficient. In the proposed design, multi-cores with small block sizes are used in parallel instead of a single core with a large block size. In addition, an appropriate pipelining schedule is proposed. Compared to the previous design, the proposed design achieves the processing speed which is closer to the target system speed, and therefore it is more efficient in hardware utilization. In addition, a scheme in which two passes of SPIHT are merged into one pass called merged refinement pass (MRP) is proposed. As the number of shifters decreases and the bit-width of remained shifters is reduced, the size of SPIHT hardware significantly decreases. The proposed FMC encoder and decoder designs achieve the throughputs of 4,448 and 4,000 Mpixels/s, respectively, and their gate counts are 76.5K and 107.8K. When the proposed design is applied to high efficiency video codec (HEVC), it achieves 1.96% lower average BDBR and 0.05 dB higher average BDPSNR than the previous FMC design.

We develop a novel SAD circuit for power-efficient H.264 encoding, namely a-SAD. Here, some highest-order MSB's are approximated to single MSB. Our theoretical estimations show that our proposed design simultaneously improves performance and power of SAD circuit, achieving good power efficiency. We decide that the optimal number of approximated MSB's is four under 8-bit YUV-420 format, the largest number not to affect video quality and compression-rate in our video experiments. In logic simulations, our a-SAD circuit shows at least 9.3% smaller critical-path delay compared to existing SAD circuits. We compare power dissipation under iso-throughput scenario, where our a-SAD circuit obtains at least 11.6% power saving compared to other designs. We perform same simulations under two- and three-stage pipelined architecture. Here, our a-SAD circuit delivers significant performance (by 13%) and power (by 17% and 15.8% for two and three stages respectively) improvements.

본 논문에서는 동영상 화질을 최대한 유지하면서 압축 비트량 절감을 효율적으로 이루기 위해 복수개의 영상처리 필터를 영상의 블록에 따라 선택적으로 적용하고, 영상처리 필터의 선택을 위한 MSSSIM(Multi-Scale Structural SIMilarity) 및 쿨백-라이블러 발산(Kullback-Leibler divergence: KL-Divergence) 기반의 영상 처리 평가 함수를 제안한다. 영상압축의 경우, 영상 내 특징에 따라 화질과 비트량 절감의 특성이 다르며, 이에 따라 단일 목적을 가진 영상처리 필터로서는 화질을 유지하면서, 비트량 절감이라는 목적을 동시에 만족 시키기 어렵다. 이에 따라, 주관적 화질을 최대한 유지하면서, 비트량을 절감시키기 위해 주관적 화질 측도로서 MSSSIM를 사용하고 비트 량 측도를 위하여 쿨백-라이블러 발산을 사용함과 동시에 두 가지 척도를 하나의 척도로 결합시키기 위한 방법을 제안한다. 아울러 제안한 측도를 사용하여 서로 다른 특성을 가진 영상처리 필터를 전처리 필터로 사용할 경우, 주관적 화질을 최대한 유지하면서 비트량 절감을 유지할 수 있도록 동영상 압축이 가능함을 확인할 수 있었다.

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.

본 논문에서는 어텐션 알고리듬 (attention algorithm) 기반의 양방향성 LSTM (bidirectional long short-term memory; BLSTM) 을 동영상의 압축 표준을 예측하기 위해 사용한다. 자연어 처리 (natural language processing; NLP) 분야에서 순환적 신경망 (recurrent neural networks; RNN) 의 구조를 이용하여 문장의 다음 단어를 예측하거나 의미에 따라 문장을 분류하거나 번역하는 연구들은 계속되어왔고, 이는 챗봇, 음성인식 스피커, 번역 애플리케이션 등으로 상용화되었다. LSTM 은 RNN에서 gradient vanishing problem 을 해결하고자 고안됐고, NLP 분야에서 유용하게 사용되고 있다. 제안한 알고리듬은 BLSTM과 특정 단어에 집중하여 분류할 수 있는 어텐션 알고리듬을 자연어 문장이 아닌 동영상의 비트스트림에 적용해 동영상의 압축 표준을 예측하는 것이 가능하다.

In this paper, we propose an Attention-based BLSTM for predicting the video compression standard of a video. Recently, in NLP, many researches have been studied to predict the next word of sentences, classify and translate sentences by their semantics using the structure of RNN, and they were commercialized as chatbots, AI speakers and translator applications, etc. LSTM is designed to solve the gradient vanishing problem in RNN, and is used in NLP. The proposed algorithm makes video compression standard prediction possible by applying BLSTM and Attention algorithm which focuses on the most important word in a sentence to a bitstream of a video, not an sentence of a natural language.

본 논문에서는 움직임 보상과 웨이브릿 변환 부호화 기법을 이용하여 비디오 신호의 데이터를 압축하고자 한다. 비디오 신호에 대한 인간 시각 특성을 분석하여 큰 이득을 주지 못하는 과정을 생략하고 인간의 눈에 민감하지 않은 정보를 생략함으로써 화질의 저하 없이 비디오 신호를 높은 비율로 압축한다. 제안한 방법은 움직임이 발생되는 정도와 크기에 매우 의존적으로, 움직임이 많은 비디오 신호에 더욱 적합하나 움직임이 작은 경우에도 저주파 대역들의 움직임 보상에 의한 이득이 크기 때문에 모든 영상에 대해서 적용 가능한 방법이다. 'football'과 'Popple'을 대상으로 한 컴퓨터 시뮬레이션결과, 프레임당 30:1 정도의 압축하에서 높은 재생화질을 얻을 수 있었다.