1,227 research outputs found

    Variable Block Size Motion Compensation In The Redundant Wavelet Domain

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    Video is one of the most powerful forms of multimedia because of the extensive information it delivers. Video sequences are highly correlated both temporally and spatially, a fact which makes the compression of video possible. Modern video systems employ motion estimation and motion compensation (ME/MC) to de-correlate a video sequence temporally. ME/MC forms a prediction of the current frame using the frames which have been already encoded. Consequently, one needs to transmit the corresponding residual image instead of the original frame, as well as a set of motion vectors which describe the scene motion as observed at the encoder. The redundant wavelet transform (RDWT) provides several advantages over the conventional wavelet transform (DWT). The RDWT overcomes the shift invariant problem in DWT. Moreover, RDWT retains all the phase information of wavelet coefficients and provides multiple prediction possibilities for ME/MC in wavelet domain. The general idea of variable size block motion compensation (VSBMC) technique is to partition a frame in such a way that regions with uniform translational motions are divided into larger blocks while those containing complicated motions into smaller blocks, leading to an adaptive distribution of motion vectors (MV) across the frame. The research proposed new adaptive partitioning schemes and decision criteria in RDWT that utilize more effectively the motion content of a frame in terms of various block sizes. The research also proposed a selective subpixel accuracy algorithm for the motion vector using a multiband approach. The selective subpixel accuracy reduces the computations produced by the conventional subpixel algorithm while maintaining the same accuracy. In addition, the method of overlapped block motion compensation (OBMC) is used to reduce blocking artifacts. Finally, the research extends the applications of the proposed VSBMC to the 3D video sequences. The experimental results obtained here have shown that VSBMC in the RDWT domain can be a powerful tool for video compression

    ๋น„๋””์˜ค ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„์„ ์œ„ํ•œ ๋‹ค์ค‘ ๋ฒกํ„ฐ ๊ธฐ๋ฐ˜์˜ MEMC ๋ฐ ์‹ฌ์ธต CNN

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2019. 2. ์ดํ˜์žฌ.Block-based hierarchical motion estimations are widely used and are successful in generating high-quality interpolation. However, it still fails in the motion estimation of small objects when a background region moves in a different direction. This is because the motion of small objects is neglected by the down-sampling and over-smoothing operations at the top level of image pyramids in the maximum a posterior (MAP) method. Consequently, the motion vector of small objects cannot be detected at the bottom level, and therefore, the small objects often appear deformed in an interpolated frame. This thesis proposes a novel algorithm that preserves the motion vector of the small objects by adding a secondary motion vector candidate that represents the movement of the small objects. This additional candidate is always propagated from the top to the bottom layers of the image pyramid. Experimental results demonstrate that the intermediate frame interpolated by the proposed algorithm significantly improves the visual quality when compared with conventional MAP-based frame interpolation. In motion compensated frame interpolation, a repetition pattern in an image makes it difficult to derive an accurate motion vector because multiple similar local minima exist in the search space of the matching cost for motion estimation. In order to improve the accuracy of motion estimation in a repetition region, this thesis attempts a semi-global approach that exploits both local and global characteristics of a repetition region. A histogram of the motion vector candidates is built by using a voter based voting system that is more reliable than an elector based voting system. Experimental results demonstrate that the proposed method significantly outperforms the previous local approach in term of both objective peak signal-to-noise ratio (PSNR) and subjective visual quality. In video frame interpolation or motion-compensated frame rate up-conversion (MC-FRUC), motion compensation along unidirectional motion trajectories directly causes overlaps and holes issues. To solve these issues, this research presents a new algorithm for bidirectional motion compensated frame interpolation. Firstly, the proposed method generates bidirectional motion vectors from two unidirectional motion vector fields (forward and backward) obtained from the unidirectional motion estimations. It is done by projecting the forward and backward motion vectors into the interpolated frame. A comprehensive metric as an extension of the distance between a projected block and an interpolated block is proposed to compute weighted coefficients in the case when the interpolated block has multiple projected ones. Holes are filled based on vector median filter of non-hole available neighbor blocks. The proposed method outperforms existing MC-FRUC methods and removes block artifacts significantly. Video frame interpolation with a deep convolutional neural network (CNN) is also investigated in this thesis. Optical flow and video frame interpolation are considered as a chicken-egg problem such that one problem affects the other and vice versa. This thesis presents a stack of networks that are trained to estimate intermediate optical flows from the very first intermediate synthesized frame and later the very end interpolated frame is generated by the second synthesis network that is fed by stacking the very first one and two learned intermediate optical flows based warped frames. The primary benefit is that it glues two problems into one comprehensive framework that learns altogether by using both an analysis-by-synthesis technique for optical flow estimation and vice versa, CNN kernels based synthesis-by-analysis. The proposed network is the first attempt to bridge two branches of previous approaches, optical flow based synthesis and CNN kernels based synthesis into a comprehensive network. Experiments are carried out with various challenging datasets, all showing that the proposed network outperforms the state-of-the-art methods with significant margins for video frame interpolation and the estimated optical flows are accurate for challenging movements. The proposed deep video frame interpolation network to post-processing is applied to the improvement of the coding efficiency of the state-of-art video compress standard, HEVC/H.265 and experimental results prove the efficiency of the proposed network.๋ธ”๋ก ๊ธฐ๋ฐ˜ ๊ณ„์ธต์  ์›€์ง์ž„ ์ถ”์ •์€ ๊ณ ํ™”์งˆ์˜ ๋ณด๊ฐ„ ์ด๋ฏธ์ง€๋ฅผ ์ƒ์„ฑํ•  ์ˆ˜ ์žˆ์–ด ํญ๋„“๊ฒŒ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ๋ฐฐ๊ฒฝ ์˜์—ญ์ด ์›€์ง์ผ ๋•Œ, ์ž‘์€ ๋ฌผ์ฒด์— ๋Œ€ํ•œ ์›€์ง์ž„ ์ถ”์ • ์„ฑ๋Šฅ์€ ์—ฌ์ „ํžˆ ์ข‹์ง€ ์•Š๋‹ค. ์ด๋Š” maximum a posterior (MAP) ๋ฐฉ์‹์œผ๋กœ ์ด๋ฏธ์ง€ ํ”ผ๋ผ๋ฏธ๋“œ์˜ ์ตœ์ƒ์œ„ ๋ ˆ๋ฒจ์—์„œ down-sampling๊ณผ over-smoothing์œผ๋กœ ์ธํ•ด ์ž‘์€ ๋ฌผ์ฒด์˜ ์›€์ง์ž„์ด ๋ฌด์‹œ๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ์ด๋ฏธ์ง€ ํ”ผ๋ผ๋ฏธ๋“œ์˜ ์ตœํ•˜์œ„ ๋ ˆ๋ฒจ์—์„œ ์ž‘์€ ๋ฌผ์ฒด์˜ ์›€์ง์ž„ ๋ฒกํ„ฐ๋Š” ๊ฒ€์ถœ๋  ์ˆ˜ ์—†์–ด ๋ณด๊ฐ„ ์ด๋ฏธ์ง€์—์„œ ์ž‘์€ ๋ฌผ์ฒด๋Š” ์ข…์ข… ๋ณ€ํ˜•๋œ ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ธ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ž‘์€ ๋ฌผ์ฒด์˜ ์›€์ง์ž„์„ ๋‚˜ํƒ€๋‚ด๋Š” 2์ฐจ ์›€์ง์ž„ ๋ฒกํ„ฐ ํ›„๋ณด๋ฅผ ์ถ”๊ฐ€ํ•˜์—ฌ ์ž‘์€ ๋ฌผ์ฒด์˜ ์›€์ง์ž„ ๋ฒกํ„ฐ๋ฅผ ๋ณด์กดํ•˜๋Š” ์ƒˆ๋กœ์šด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ์ถ”๊ฐ€๋œ ์›€์ง์ž„ ๋ฒกํ„ฐ ํ›„๋ณด๋Š” ํ•ญ์ƒ ์ด๋ฏธ์ง€ ํ”ผ๋ผ๋ฏธ๋“œ์˜ ์ตœ์ƒ์œ„์—์„œ ์ตœํ•˜์œ„ ๋ ˆ๋ฒจ๋กœ ์ „ํŒŒ๋œ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ์ œ์•ˆ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๋ณด๊ฐ„ ์ƒ์„ฑ ํ”„๋ ˆ์ž„์ด ๊ธฐ์กด MAP ๊ธฐ๋ฐ˜ ๋ณด๊ฐ„ ๋ฐฉ์‹์œผ๋กœ ์ƒ์„ฑ๋œ ํ”„๋ ˆ์ž„๋ณด๋‹ค ์ด๋ฏธ์ง€ ํ™”์งˆ์ด ์ƒ๋‹นํžˆ ํ–ฅ์ƒ๋จ์„ ๋ณด์—ฌ์ค€๋‹ค. ์›€์ง์ž„ ๋ณด์ƒ ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„์—์„œ, ์ด๋ฏธ์ง€ ๋‚ด์˜ ๋ฐ˜๋ณต ํŒจํ„ด์€ ์›€์ง์ž„ ์ถ”์ •์„ ์œ„ํ•œ ์ •ํ•ฉ ์˜ค์ฐจ ํƒ์ƒ‰ ์‹œ ๋‹ค์ˆ˜์˜ ์œ ์‚ฌ local minima๊ฐ€ ์กด์žฌํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ •ํ™•ํ•œ ์›€์ง์ž„ ๋ฒกํ„ฐ ์œ ๋„๋ฅผ ์–ด๋ ต๊ฒŒ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋ฐ˜๋ณต ํŒจํ„ด์—์„œ์˜ ์›€์ง์ž„ ์ถ”์ •์˜ ์ •ํ™•๋„๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋ฐ˜๋ณต ์˜์—ญ์˜ localํ•œ ํŠน์„ฑ๊ณผ globalํ•œ ํŠน์„ฑ์„ ๋™์‹œ์— ํ™œ์šฉํ•˜๋Š” semi-globalํ•œ ์ ‘๊ทผ์„ ์‹œ๋„ํ•œ๋‹ค. ์›€์ง์ž„ ๋ฒกํ„ฐ ํ›„๋ณด์˜ ํžˆ์Šคํ† ๊ทธ๋žจ์€ ์„ ๊ฑฐ ๊ธฐ๋ฐ˜ ํˆฌํ‘œ ์‹œ์Šคํ…œ๋ณด๋‹ค ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ์œ ๊ถŒ์ž ๊ธฐ๋ฐ˜ ํˆฌํ‘œ ์‹œ์Šคํ…œ ๊ธฐ๋ฐ˜์œผ๋กœ ํ˜•์„ฑ๋œ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์ด ์ด์ „์˜ localํ•œ ์ ‘๊ทผ๋ฒ•๋ณด๋‹ค peak signal-to-noise ratio (PSNR)์™€ ์ฃผ๊ด€์  ํ™”์งˆ ํŒ๋‹จ ๊ด€์ ์—์„œ ์ƒ๋‹นํžˆ ์šฐ์ˆ˜ํ•จ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋น„๋””์˜ค ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„ ๋˜๋Š” ์›€์ง์ž„ ๋ณด์ƒ ํ”„๋ ˆ์ž„์œจ ์ƒํ–ฅ ๋ณ€ํ™˜ (MC-FRUC)์—์„œ, ๋‹จ๋ฐฉํ–ฅ ์›€์ง์ž„ ๊ถค์ ์— ๋”ฐ๋ฅธ ์›€์ง์ž„ ๋ณด์ƒ์€ overlap๊ณผ hole ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚จ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์–‘๋ฐฉํ–ฅ ์›€์ง์ž„ ๋ณด์ƒ ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. ๋จผ์ €, ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ๋‹จ๋ฐฉํ–ฅ ์›€์ง์ž„ ์ถ”์ •์œผ๋กœ๋ถ€ํ„ฐ ์–ป์–ด์ง„ ๋‘ ๊ฐœ์˜ ๋‹จ๋ฐฉํ–ฅ ์›€์ง์ž„ ์˜์—ญ(์ „๋ฐฉ ๋ฐ ํ›„๋ฐฉ)์œผ๋กœ๋ถ€ํ„ฐ ์–‘๋ฐฉํ–ฅ ์›€์ง์ž„ ๋ฒกํ„ฐ๋ฅผ ์ƒ์„ฑํ•œ๋‹ค. ์ด๋Š” ์ „๋ฐฉ ๋ฐ ํ›„๋ฐฉ ์›€์ง์ž„ ๋ฒกํ„ฐ๋ฅผ ๋ณด๊ฐ„ ํ”„๋ ˆ์ž„์— ํˆฌ์˜ํ•จ์œผ๋กœ์จ ์ˆ˜ํ–‰๋œ๋‹ค. ๋ณด๊ฐ„๋œ ๋ธ”๋ก์— ์—ฌ๋Ÿฌ ๊ฐœ์˜ ํˆฌ์˜๋œ ๋ธ”๋ก์ด ์žˆ๋Š” ๊ฒฝ์šฐ, ํˆฌ์˜๋œ ๋ธ”๋ก๊ณผ ๋ณด๊ฐ„๋œ ๋ธ”๋ก ์‚ฌ์ด์˜ ๊ฑฐ๋ฆฌ๋ฅผ ํ™•์žฅํ•˜๋Š” ๊ธฐ์ค€์ด ๊ฐ€์ค‘ ๊ณ„์ˆ˜๋ฅผ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋œ๋‹ค. Hole์€ hole์ด ์•„๋‹Œ ์ด์›ƒ ๋ธ”๋ก์˜ vector median filter๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฒ˜๋ฆฌ๋œ๋‹ค. ์ œ์•ˆ ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์˜ MC-FRUC๋ณด๋‹ค ์„ฑ๋Šฅ์ด ์šฐ์ˆ˜ํ•˜๋ฉฐ, ๋ธ”๋ก ์—ดํ™”๋ฅผ ์ƒ๋‹นํžˆ ์ œ๊ฑฐํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” CNN์„ ์ด์šฉํ•œ ๋น„๋””์˜ค ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„์— ๋Œ€ํ•ด์„œ๋„ ๋‹ค๋ฃฌ๋‹ค. Optical flow ๋ฐ ๋น„๋””์˜ค ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„์€ ํ•œ ๊ฐ€์ง€ ๋ฌธ์ œ๊ฐ€ ๋‹ค๋ฅธ ๋ฌธ์ œ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” chicken-egg ๋ฌธ์ œ๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ค‘๊ฐ„ optical flow ๋ฅผ ๊ณ„์‚ฐํ•˜๋Š” ๋„คํŠธ์›Œํฌ์™€ ๋ณด๊ฐ„ ํ”„๋ ˆ์ž„์„ ํ•ฉ์„ฑ ํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๋„คํŠธ์›Œํฌ๋กœ ์ด๋ฃจ์–ด์ง„ ํ•˜๋‚˜์˜ ๋„คํŠธ์›Œํฌ ์Šคํƒ์„ ๊ตฌ์กฐ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. The final ๋ณด๊ฐ„ ํ”„๋ ˆ์ž„์„ ์ƒ์„ฑํ•˜๋Š” ๋„คํŠธ์›Œํฌ์˜ ๊ฒฝ์šฐ ์ฒซ ๋ฒˆ์งธ ๋„คํŠธ์›Œํฌ์˜ ์ถœ๋ ฅ์ธ ๋ณด๊ฐ„ ํ”„๋ ˆ์ž„ ์™€ ์ค‘๊ฐ„ optical flow based warped frames์„ ์ž…๋ ฅ์œผ๋กœ ๋ฐ›์•„์„œ ํ”„๋ ˆ์ž„์„ ์ƒ์„ฑํ•œ๋‹ค. ์ œ์•ˆ๋œ ๊ตฌ์กฐ์˜ ๊ฐ€์žฅ ํฐ ํŠน์ง•์€ optical flow ๊ณ„์‚ฐ์„ ์œ„ํ•œ ํ•ฉ์„ฑ์— ์˜ํ•œ ๋ถ„์„๋ฒ•๊ณผ CNN ๊ธฐ๋ฐ˜์˜ ๋ถ„์„์— ์˜ํ•œ ํ•ฉ์„ฑ๋ฒ•์„ ๋ชจ๋‘ ์ด์šฉํ•˜์—ฌ ํ•˜๋‚˜์˜ ์ข…ํ•ฉ์ ์ธ framework๋กœ ๊ฒฐํ•ฉํ•˜์˜€๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์ œ์•ˆ๋œ ๋„คํŠธ์›Œํฌ๋Š” ๊ธฐ์กด์˜ ๋‘ ๊ฐ€์ง€ ์—ฐ๊ตฌ์ธ optical flow ๊ธฐ๋ฐ˜ ํ”„๋ ˆ์ž„ ํ•ฉ์„ฑ๊ณผ CNN ๊ธฐ๋ฐ˜ ํ•ฉ์„ฑ ํ”„๋ ˆ์ž„ ํ•ฉ์„ฑ๋ฒ•์„ ์ฒ˜์Œ ๊ฒฐํ•ฉ์‹œํ‚จ ๋ฐฉ์‹์ด๋‹ค. ์‹คํ—˜์€ ๋‹ค์–‘ํ•˜๊ณ  ๋ณต์žกํ•œ ๋ฐ์ดํ„ฐ ์…‹์œผ๋กœ ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ, ๋ณด๊ฐ„ ํ”„๋ ˆ์ž„ quality ์™€ optical flow ๊ณ„์‚ฐ ์ •ํ™•๋„ ์ธก๋ฉด์—์„œ ๊ธฐ์กด์˜ state-of-art ๋ฐฉ์‹์— ๋น„ํ•ด ์›”๋“ฑํžˆ ๋†’์€ ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ํ›„ ์ฒ˜๋ฆฌ๋ฅผ ์œ„ํ•œ ์‹ฌ์ธต ๋น„๋””์˜ค ํ”„๋ ˆ์ž„ ๋ณด๊ฐ„ ๋„คํŠธ์›Œํฌ๋Š” ์ฝ”๋”ฉ ํšจ์œจ ํ–ฅ์ƒ์„ ์œ„ํ•ด ์ตœ์‹  ๋น„๋””์˜ค ์••์ถ• ํ‘œ์ค€์ธ HEVC/H.265์— ์ ์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ์ œ์•ˆ ๋„คํŠธ์›Œํฌ์˜ ํšจ์œจ์„ฑ์„ ์ž…์ฆํ•œ๋‹ค.Abstract i Table of Contents iv List of Tables vii List of Figures viii Chapter 1. Introduction 1 1.1. Hierarchical Motion Estimation of Small Objects 2 1.2. Motion Estimation of a Repetition Pattern Region 4 1.3. Motion-Compensated Frame Interpolation 5 1.4. Video Frame Interpolation with Deep CNN 6 1.5. Outline of the Thesis 7 Chapter 2. Previous Works 9 2.1. Previous Works on Hierarchical Block-Based Motion Estimation 9 2.1.1.โ€‚Maximum a Posterior (MAP) Framework 10 2.1.2.Hierarchical Motion Estimation 12 2.2. Previous Works on Motion Estimation for a Repetition Pattern Region 13 2.3. Previous Works on Motion Compensation 14 2.4. Previous Works on Video Frame Interpolation with Deep CNN 16 Chapter 3. Hierarchical Motion Estimation for Small Objects 19 3.1. Problem Statement 19 3.2. The Alternative Motion Vector of High Cost Pixels 20 3.3. Modified Hierarchical Motion Estimation 23 3.4. Framework of the Proposed Algorithm 24 3.5. Experimental Results 25 3.5.1. Performance Analysis 26 3.5.2. Performance Evaluation 29 Chapter 4. Semi-Global Accurate Motion Estimation for a Repetition Pattern Region 32 4.1. Problem Statement 32 4.2. Objective Function and Constrains 33 4.3. Elector based Voting System 34 4.4. Voter based Voting System 36 4.5. Experimental Results 40 Chapter 5. Multiple Motion Vectors based Motion Compensation 44 5.1. Problem Statement 44 5.2. Adaptive Weighted Multiple Motion Vectors based Motion Compensation 45 5.2.1. One-to-Multiple Motion Vector Projection 45 5.2.2. A Comprehensive Metric as the Extension of Distance 48 5.3. Handling Hole Blocks 49 5.4. Framework of the Proposed Motion Compensated Frame Interpolation 50 5.5. Experimental Results 51 Chapter 6. Video Frame Interpolation with a Stack of Deep CNN 56 6.1. Problem Statement 56 6.2. The Proposed Network for Video Frame Interpolation 57 6.2.1. A Stack of Synthesis Networks 57 6.2.2. Intermediate Optical Flow Derivation Module 60 6.2.3. Warping Operations 62 6.2.4. Training and Loss Function 63 6.2.5. Network Architecture 64 6.2.6. Experimental Results 64 6.2.6.1. Frame Interpolation Evaluation 64 6.2.6.2. Ablation Experiments 77 6.3. Extension for Quality Enhancement for Compressed Videos Task 83 6.4. Extension for Improving the Coding Efficiency of HEVC based Low Bitrate Encoder 88 Chapter 7. Conclusion 94 References 97Docto

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    Common strategies for detection and tracking of aerial moving targets in airborne Forward-Looking Infrared (FLIR) images offer accurate results in images composed by a non-textured sky. However, when cloud and earth regions appear in the image sequence, those strategies result in an over-detection that increases very significantly the false alarm rate. Besides, the airborne camera induces a global motion in the image sequence that complicates even more detection and tracking tasks. In this work, an automatic detection and tracking system with an innovative and efficient target trajectory filtering is presented. It robustly compensates the global motion to accurately detect and track potential aerial targets. Their trajectories are analyzed by a curve fitting technique to reliably validate real targets. This strategy allows to filter false targets with stationary or erratic trajectories. The proposed system makes special emphasis in the use of low complexity video analysis techniques to achieve real-time operation. Experimental results using real FLIR sequences show a dramatic reduction of the false alarm rate, while maintaining the detection rate

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    The aim of this research is to develop algorithms for enhancing the subjective quality and coding efficiency of standard block-based video coders. In the past few years, numerous video coding standards based on motion-compensated block-transform structure have been established where block-based motion estimation is used for reducing the correlation between consecutive images and block transform is used for coding the resulting motion-compensated residual images. Due to the use of predictive differential coding and variable length coding techniques, the output data rate exhibits extreme fluctuations. A rate control algorithm is devised for achieving a stable output data rate. This rate control algorithm, which is essentially a bit-rate estimation algorithm, is then employed in a bit-allocation algorithm for improving the visual quality of the coded images, based on some prior knowledge of the images. Block-based hybrid coders achieve high compression ratio mainly due to the employment of a motion estimation and compensation stage in the coding process. The conventional bit-allocation strategy for these coders simply assigns the bits required by the motion vectors and the rest to the residual image. However, at very low bit-rates, this bit-allocation strategy is inadequate as the motion vector bits takes up a considerable portion of the total bit-rate. A rate-constrained selection algorithm is presented where an analysis-by-synthesis approach is used for choosing the best motion vectors in term of resulting bit rate and image quality. This selection algorithm is then implemented for mode selection. A simple algorithm based on the above-mentioned bit-rate estimation algorithm is developed for the latter to reduce the computational complexity. For very low bit-rate applications, it is well-known that block-based coders suffer from blocking artifacts. A coding mode is presented for reducing these annoying artifacts by coding a down-sampled version of the residual image with a smaller quantisation step size. Its applications for adaptive source/channel coding and for coding fast changing sequences are examined

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    With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2-D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. [Continues.

    A family of stereoscopic image compression algorithms using wavelet transforms

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    With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. In the proposed CODEC I, block-based disparity estimation/compensation (DE/DC) is performed in pixel domain. However, this results in an inefficiency when DWT is applied on the whole predictive error image that results from the DE process. This is because of the existence of artificial block boundaries between error blocks in the predictive error image. To overcome this problem, in the remaining proposed CODECs, DE/DC is performed in the wavelet domain. Due to the multiresolution nature of the wavelet domain, two methods of disparity estimation and compensation have been proposed. The first method is performing DEJDC in each subband of the lowest/coarsest resolution level and then propagating the disparity vectors obtained to the corresponding subbands of higher/finer resolution. Note that DE is not performed in every subband due to the high overhead bits that could be required for the coding of disparity vectors of all subbands. This method is being used in CODEC II. In the second method, DEJDC is performed m the wavelet-block domain. This enables disparity estimation to be performed m all subbands simultaneously without increasing the overhead bits required for the coding disparity vectors. This method is used by CODEC III. However, performing disparity estimation/compensation in all subbands would result in a significant improvement of CODEC III. To further improve the performance of CODEC ill, pioneering wavelet-block search technique is implemented in CODEC IV. The pioneering wavelet-block search technique enables the right/predicted image to be reconstructed at the decoder end without the need of transmitting the disparity vectors. In proposed CODEC V, pioneering block search is performed in all subbands of DWT decomposition which results in an improvement of its performance. Further, the CODEC IV and V are able to perform at very low bit rates(< 0.15 bpp). In CODEC VI and CODEC VII, Overlapped Block Disparity Compensation (OBDC) is used with & without the need of coding disparity vector. Our experiment results showed that no significant coding gains could be obtained for these CODECs over CODEC IV & V. All proposed CODECs m this thesis are wavelet-based stereo image coding algorithms that maximise the flexibility and benefits offered by wavelet transform technology when applied to stereo imaging. In addition the use of a baseline-JPEG coding architecture would enable the easy adaptation of the proposed algorithms within systems originally built for DCT-based coding. This is an important feature that would be useful during an era where DCT-based technology is only slowly being phased out to give way for DWT based compression technology. In addition, this thesis proposed a stereo image coding algorithm that uses JPEG-2000 technology as the basic compression engine. The proposed CODEC, named RASTER is a rate scalable stereo image CODEC that has a unique ability to preserve the image quality at binocular depth boundaries, which is an important requirement in the design of stereo image CODEC. The experimental results have shown that the proposed CODEC is able to achieve PSNR gains of up to 3.7 dB as compared to directly transmitting the right frame using JPEG-2000
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