3 research outputs found

    Image and Video Coding Techniques for Ultra-low Latency

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    The next generation of wireless networks fosters the adoption of latency-critical applications such as XR, connected industry, or autonomous driving. This survey gathers implementation aspects of different image and video coding schemes and discusses their tradeoffs. Standardized video coding technologies such as HEVC or VVC provide a high compression ratio, but their enormous complexity sets the scene for alternative approaches like still image, mezzanine, or texture compression in scenarios with tight resource or latency constraints. Regardless of the coding scheme, we found inter-device memory transfers and the lack of sub-frame coding as limitations of current full-system and software-programmable implementations.publishedVersionPeer reviewe

    ๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜๋ฅผ ์œ„ํ•œ ๊ณ ์ • ๋น„์œจ ์••์ถ• ํ•˜๋“œ์›จ์–ด ์„ค๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2016. 2. ์ดํ˜์žฌ.๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜์—์„œ์˜ ์••์ถ• ๋ฐฉ์‹์€ ์ผ๋ฐ˜์ ์ธ ๋น„๋””์˜ค ์••์ถ• ํ‘œ์ค€๊ณผ๋Š” ๋‹ค๋ฅธ ๋ช‡ ๊ฐ€์ง€ ํŠน์ง•์ด ์žˆ๋‹ค. ์ฒซ์งธ, ํŠน์ˆ˜ํ•œ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๋‘˜์งธ, ์••์ถ• ์ด๋“, ์†Œ๋น„ ์ „๋ ฅ, ์‹ค์‹œ๊ฐ„ ์ฒ˜๋ฆฌ ๋“ฑ์„ ์œ„ํ•ด ํ•˜๋“œ์›จ์–ด ํฌ๊ธฐ๊ฐ€ ์ž‘๊ณ , ๋ชฉํ‘œ๋กœ ํ•˜๋Š” ์••์ถ•๋ฅ ์ด ๋‚ฎ๋‹ค. ์…‹์งธ, ๋ž˜์Šคํ„ฐ ์ฃผ์‚ฌ ์ˆœ์„œ์— ์ ํ•ฉํ•ด์•ผ ํ•œ๋‹ค. ๋„ท์งธ, ํ”„๋ ˆ์ž„ ๋ฉ”๋ชจ๋ฆฌ ํฌ๊ธฐ๋ฅผ ์ œํ•œ์‹œํ‚ค๊ฑฐ๋‚˜ ์ž„์˜ ์ ‘๊ทผ์„ ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์••์ถ• ๋‹จ์œ„๋‹น ๋ชฉํ‘œ ์••์ถ•๋ฅ ์„ ์‹ค์‹œ๊ฐ„์œผ๋กœ ์ •ํ™•ํžˆ ๋งž์ถœ ์ˆ˜ ์žˆ์–ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด์™€ ๊ฐ™์€ ํŠน์ง•์„ ๋งŒ์กฑ์‹œํ‚ค๋Š” ์„ธ ๊ฐ€์ง€ ์••์ถ• ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ๋ฅผ ์ œ์•ˆํ•˜๋„๋ก ํ•œ๋‹ค. LCD ์˜ค๋ฒ„๋“œ๋ผ์ด๋ธŒ๋ฅผ ์œ„ํ•œ ์••์ถ• ๋ฐฉ์‹์œผ๋กœ๋Š” BTC(block truncation coding) ๊ธฐ๋ฐ˜์˜ ์••์ถ• ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋„๋ก ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์••์ถ• ์ด๋“์„ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ ๋ชฉํ‘œ ์••์ถ•๋ฅ  12์— ๋Œ€ํ•œ ์••์ถ• ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋Š”๋ฐ, ์••์ถ• ํšจ์œจ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€ ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ด์›ƒํ•˜๋Š” ๋ธ”๋ก๊ณผ์˜ ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ์„ ์ด์šฉํ•˜์—ฌ ๋น„ํŠธ๋ฅผ ์ ˆ์•ฝํ•˜๋Š” ๋ฐฉ๋ฒ•์ด๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋‘ ๋ฒˆ์งธ๋Š” ๋‹จ์ˆœํ•œ ์˜์—ญ์€ 2ร—16 ์ฝ”๋”ฉ ๋ธ”๋ก, ๋ณต์žกํ•œ ์˜์—ญ์€ 2ร—8 ์ฝ”๋”ฉ ๋ธ”๋ก์„ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์ด๋‹ค. 2ร—8 ์ฝ”๋”ฉ ๋ธ”๋ก์„ ์ด์šฉํ•˜๋Š” ๊ฒฝ์šฐ ๋ชฉํ‘œ ์••์ถ•๋ฅ ์„ ๋งž์ถ”๊ธฐ ์œ„ํ•˜์—ฌ ์ฒซ ๋ฒˆ์งธ ๋ฐฉ๋ฒ•์œผ๋กœ ์ ˆ์•ฝ๋œ ๋น„ํŠธ๋ฅผ ์ด์šฉํ•œ๋‹ค. ์ €๋น„์šฉ ๊ทผ์ ‘-๋ฌด์†์‹ค ํ”„๋ ˆ์ž„ ๋ฉ”๋ชจ๋ฆฌ ์••์ถ•์„ ์œ„ํ•œ ๋ฐฉ์‹์œผ๋กœ๋Š” 1D SPIHT(set partitioning in hierarchical trees) ๊ธฐ๋ฐ˜์˜ ์••์ถ• ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋„๋ก ํ•œ๋‹ค. SPIHT์€ ๊ณ ์ • ๋ชฉํ‘œ ์••์ถ•๋ฅ ์„ ๋งž์ถ”๋Š”๋ฐ ๋งค์šฐ ํšจ๊ณผ์ ์ธ ์••์ถ• ๋ฐฉ์‹์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ 1D ํ˜•ํƒœ์ธ 1D SPIHT์€ ๋ž˜์Šคํ„ฐ ์ฃผ์‚ฌ ์ˆœ์„œ์— ์ ํ•ฉํ•จ์—๋„ ๊ด€๋ จ ์—ฐ๊ตฌ๊ฐ€ ๋งŽ์ด ์ง„ํ–‰๋˜์ง€ ์•Š์•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ 1D SPIHT์˜ ๊ฐ€์žฅ ํฐ ๋ฌธ์ œ์ ์ธ ์†๋„ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ๋Š” ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด 1D SPIHT ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๋ณ‘๋ ฌ์„ฑ์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ˜•ํƒœ๋กœ ์ˆ˜์ •๋œ๋‹ค. ์ธ์ฝ”๋”์˜ ๊ฒฝ์šฐ ๋ณ‘๋ ฌ ์ฒ˜๋ฆฌ๋ฅผ ๋ฐฉํ•ดํ•˜๋Š” ์˜์กด ๊ด€๊ณ„๊ฐ€ ํ•ด๊ฒฐ๋˜๊ณ , ํŒŒ์ดํ”„๋ผ์ธ ์Šค์ผ€์ฅด๋ง์ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋œ๋‹ค. ๋””์ฝ”๋”์˜ ๊ฒฝ์šฐ ๋ณ‘๋ ฌ๋กœ ๋™์ž‘ํ•˜๋Š” ๊ฐ ํŒจ์Šค๊ฐ€ ๋””์ฝ”๋”ฉํ•  ๋น„ํŠธ์ŠคํŠธ๋ฆผ์˜ ๊ธธ์ด๋ฅผ ๋ฏธ๋ฆฌ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋„๋ก ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ˆ˜์ •๋œ๋‹ค. ๊ณ ์ถฉ์‹ค๋„(high-fidelity) RGBW ์ปฌ๋Ÿฌ ์ด๋ฏธ์ง€ ์••์ถ•์„ ์œ„ํ•œ ๋ฐฉ์‹์œผ๋กœ๋Š” ์˜ˆ์ธก ๊ธฐ๋ฐ˜์˜ ์••์ถ• ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋„๋ก ํ•œ๋‹ค. ์ œ์•ˆ ์˜ˆ์ธก ๋ฐฉ์‹์€ ๋‘ ๋‹จ๊ณ„์˜ ์ฐจ๋ถ„ ๊ณผ์ •์œผ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ์„ ์ด์šฉํ•˜๋Š” ๋‹จ๊ณ„์ด๊ณ , ๋‘ ๋ฒˆ์งธ๋Š” ์ธํ„ฐ-์ปฌ๋Ÿฌ ์—ฐ๊ด€์„ฑ์„ ์ด์šฉํ•˜๋Š” ๋‹จ๊ณ„์ด๋‹ค. ์ฝ”๋”ฉ์˜ ๊ฒฝ์šฐ ์••์ถ• ํšจ์œจ์ด ๋†’์€ VLC(variable length coding) ๋ฐฉ์‹์„ ์ด์šฉํ•˜๋„๋ก ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด์˜ VLC ๋ฐฉ์‹์€ ๋ชฉํ‘œ ์••์ถ•๋ฅ ์„ ์ •ํ™•ํžˆ ๋งž์ถ”๋Š”๋ฐ ์–ด๋ ค์›€์ด ์žˆ์—ˆ์œผ๋ฏ€๋กœ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Golomb-Rice ์ฝ”๋”ฉ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๊ณ ์ • ๊ธธ์ด ์••์ถ• ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋„๋ก ํ•œ๋‹ค. ์ œ์•ˆ ์ธ์ฝ”๋”๋Š” ํ”„๋ฆฌ-์ฝ”๋”์™€ ํฌ์Šคํ„ฐ-์ฝ”๋”๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋‹ค. ํ”„๋ฆฌ-์ฝ”๋”๋Š” ํŠน์ • ์ƒํ™ฉ์— ๋Œ€ํ•˜์—ฌ ์‹ค์ œ ์ธ์ฝ”๋”ฉ์„ ์ˆ˜ํ–‰ํ•˜๊ณ , ๋‹ค๋ฅธ ๋ชจ๋“  ์ƒํ™ฉ์— ๋Œ€ํ•œ ์˜ˆ์ธก ์ธ์ฝ”๋”ฉ ์ •๋ณด๋ฅผ ๊ณ„์‚ฐํ•˜์—ฌ ํฌ์Šคํ„ฐ-์ฝ”๋”์— ์ „๋‹ฌํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํฌ์ŠคํŠธ-์ฝ”๋”๋Š” ์ „๋‹ฌ๋ฐ›์€ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜์—ฌ ์‹ค์ œ ๋น„ํŠธ์ŠคํŠธ๋ฆผ์„ ์ƒ์„ฑํ•œ๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ ๋‚ด์šฉ 4 1.3 ๋…ผ๋ฌธ ๊ตฌ์„ฑ 8 ์ œ 2 ์žฅ ์ด์ „ ์—ฐ๊ตฌ 9 2.1 BTC 9 2.1.1 ๊ธฐ๋ณธ BTC ์•Œ๊ณ ๋ฆฌ์ฆ˜ 9 2.1.2 ์ปฌ๋Ÿฌ ์ด๋ฏธ์ง€ ์••์ถ•์„ ์œ„ํ•œ BTC ์•Œ๊ณ ๋ฆฌ์ฆ˜ 10 2.2 SPIHT 13 2.2.1 1D SPIHT ์•Œ๊ณ ๋ฆฌ์ฆ˜ 13 2.2.2 SPIHT ํ•˜๋“œ์›จ์–ด 17 2.3 ์˜ˆ์ธก ๊ธฐ๋ฐ˜ ์ฝ”๋”ฉ 19 2.3.1 ์˜ˆ์ธก ๋ฐฉ๋ฒ• 19 2.3.2 VLC 20 2.3.3 ์˜ˆ์ธก ๊ธฐ๋ฐ˜ ์ฝ”๋”ฉ ํ•˜๋“œ์›จ์–ด 22 ์ œ 3 ์žฅ LCD ์˜ค๋ฒ„๋“œ๋ผ์ด๋ธŒ๋ฅผ ์œ„ํ•œ BTC 24 3.1 ์ œ์•ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜ 24 3.1.1 ๋น„ํŠธ-์ ˆ์•ฝ ๋ฐฉ๋ฒ• 25 3.1.2 ๋ธ”๋ก ํฌ๊ธฐ ์„ ํƒ ๋ฐฉ๋ฒ• 29 3.1.3 ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์š”์•ฝ 31 3.2 ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ 33 3.2.1 ํ”„๋ ˆ์ž„ ๋ฉ”๋ชจ๋ฆฌ ์ธํ„ฐํŽ˜์ด์Šค 34 3.2.2 ์ธ์ฝ”๋”์™€ ๋””์ฝ”๋”์˜ ๊ตฌ์กฐ 37 3.3 ์‹คํ—˜ ๊ฒฐ๊ณผ 44 3.3.1 ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์„ฑ๋Šฅ 44 3.3.2 ํ•˜๋“œ์›จ์–ด ๊ตฌํ˜„ ๊ฒฐ๊ณผ 49 ์ œ 4 ์žฅ ์ €๋น„์šฉ ๊ทผ์ ‘-๋ฌด์†์‹ค ํ”„๋ ˆ์ž„ ๋ฉ”๋ชจ๋ฆฌ ์••์ถ•์„ ์œ„ํ•œ ๊ณ ์† 1D SPIHT 54 4.1 ์ธ์ฝ”๋” ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ 54 4.1.1 ์˜์กด ๊ด€๊ณ„ ๋ถ„์„ ๋ฐ ์ œ์•ˆํ•˜๋Š” ํŒŒ์ดํ”„๋ผ์ธ ์Šค์ผ€์ฅด 54 4.1.2 ๋ถ„๋ฅ˜ ๋น„ํŠธ ์žฌ๋ฐฐ์น˜ 57 4.2 ๋””์ฝ”๋” ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ 59 4.2.1 ๋น„ํŠธ์ŠคํŠธ๋ฆผ์˜ ์‹œ์ž‘ ์ฃผ์†Œ ๊ณ„์‚ฐ 59 4.2.2 ์ ˆ๋ฐ˜-ํŒจ์Šค ์ฒ˜๋ฆฌ ๋ฐฉ๋ฒ• 63 4.3 ํ•˜๋“œ์›จ์–ด ๊ตฌํ˜„ 65 4.4 ์‹คํ—˜ ๊ฒฐ๊ณผ 73 ์ œ 5 ์žฅ ๊ณ ์ถฉ์‹ค๋„ RGBW ์ปฌ๋Ÿฌ ์ด๋ฏธ์ง€ ์••์ถ•์„ ์œ„ํ•œ ๊ณ ์ • ์••์ถ•๋น„ VLC 81 5.1 ์ œ์•ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜ 81 5.1.1 RGBW ์ธํ„ฐ-์ปฌ๋Ÿฌ ์—ฐ๊ด€์„ฑ์„ ์ด์šฉํ•œ ์˜ˆ์ธก ๋ฐฉ์‹ 82 5.1.2 ๊ณ ์ • ์••์ถ•๋น„๋ฅผ ์œ„ํ•œ Golomb-Rice ์ฝ”๋”ฉ 85 5.1.3 ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์š”์•ฝ 89 5.2 ํ•˜๋“œ์›จ์–ด ๊ตฌ์กฐ 90 5.2.1 ์ธ์ฝ”๋” ๊ตฌ์กฐ 91 5.2.2 ๋””์ฝ”๋” ๊ตฌ์กฐ 95 5.3 ์‹คํ—˜ ๊ฒฐ๊ณผ 101 5.3.1 ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์‹คํ—˜ ๊ฒฐ๊ณผ 101 5.3.2 ํ•˜๋“œ์›จ์–ด ๊ตฌํ˜„ ๊ฒฐ๊ณผ 107 ์ œ 6 ์žฅ ์••์ถ• ์„ฑ๋Šฅ ๋ฐ ํ•˜๋“œ์›จ์–ด ํฌ๊ธฐ ๋น„๊ต ๋ถ„์„ 113 6.1 ์••์ถ• ์„ฑ๋Šฅ ๋น„๊ต 113 6.2 ํ•˜๋“œ์›จ์–ด ํฌ๊ธฐ ๋น„๊ต 120 ์ œ 7 ์žฅ ๊ฒฐ๋ก  125 ์ฐธ๊ณ ๋ฌธํ—Œ 128 ABSTRACT 135Docto
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