{"id":41842,"date":"2020-02-17T05:33:02","date_gmt":"2020-02-17T02:33:02","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/novyj-proekt-dlya-udaleniya-artefaktov-iz-jpeg"},"modified":"2020-02-17T05:33:02","modified_gmt":"2020-02-17T02:33:02","slug":"novyj-proekt-dlya-udaleniya-artefaktov-iz-jpeg","status":"publish","type":"post","link":"https:\/\/prohoster.info\/ro\/blog\/novyj-proekt-dlya-udaleniya-artefaktov-iz-jpeg","title":{"rendered":"Un nou proiect pentru eliminarea artefactelor din JPEG","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Proiectul a fost publicat pe GitHub JPEG Quant Smooth<\/a><\/noindex>, destinat s\u0103 elimine artefactele de compresie din imaginile JPEG. Acest lucru se realizeaz\u0103 prin restabilirea preciziei coeficientilor transform\u0103rii cosinus discrete. Totu\u0219i, \u00een limitele permise de tabela de cuantizare, acest lucru nu permite algoritmului s\u0103 reprocesese imaginea. Codul este scris \u00een C cu optimiz\u0103ri pentru SSE2, AVX2 \u0219i ARM Neon. De asemenea, disponibil\u0103<\/a><\/noindex> exist\u0103 o versiune WebAssembly care permite procesarea imaginilor \u00een browser (dar este mai lent\u0103 dec\u00e2t versiunea nativ\u0103 din cauza lipsei optimiz\u0103rilor SIMD \u0219i a multiproces\u0103rii).<\/p>\n

Potrivit autorului, algoritmul s\u0103u func\u021bioneaz\u0103 semnificativ mai repede dec\u00e2t un proiect similar jpeg2png<\/a><\/noindex> \u0219i produce imagini mai clare. Totu\u0219i, autorul recunoa\u0219te c\u0103 jpeg2png ar putea performa mai bine \u00een cazuri complexe. Alt proiect, knusperli<\/a><\/noindex>, publicat sub contul Google \u2014 care ar trebui s\u0103 elimine artefactele JPEG, conform autorului \u201enu este de niciun folos\u201d \u0219i \u201eeste greu de observat \u00eembun\u0103t\u0103\u021birile aduse de acesta.\u201d<\/p>\n

\"Un<\/a><\/noindex>\"Un<\/a><\/noindex><\/center><\/p>\n

\"Un<\/a><\/noindex>\"Un<\/a><\/noindex><\/center><\/p>\n

<\/a><\/noindex><\/p>\n

Sursa: opennet.ro<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041d\u0430 GitHub \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d \u043f\u0440\u043e\u0435\u043a\u0442 JPEG Quant Smooth, \u043f\u0440\u0435\u0434\u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044b\u0439 \u0434\u043b\u044f \u0443\u0434\u0430\u043b\u0435\u043d\u0438\u044f \u0430\u0440\u0442\u0435\u0444\u0430\u043a\u0442\u043e\u0432 \u0441\u0436\u0430\u0442\u0438\u044f \u0438\u0437 JPEG-\u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439. \u042d\u0442\u043e \u0434\u043e\u0441\u0442\u0438\u0433\u0430\u0435\u0442\u0441\u044f \u0437\u0430 \u0441\u0447\u0451\u0442 \u0432\u043e\u0441\u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u043e\u0432 \u0434\u0438\u0441\u043a\u0440\u0435\u0442\u043d\u043e\u0433\u043e \u043a\u043e\u0441\u0438\u043d\u0443\u0441 \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f. \u041d\u043e \u0432 \u0442\u0435\u0445 \u043f\u0440\u0435\u0434\u0435\u043b\u0430\u0445, \u0447\u0442\u043e \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0442\u0430\u0431\u043b\u0438\u0446\u0430 \u043a\u0432\u0430\u043d\u0442\u0438\u0437\u0430\u0446\u0438\u0438, \u044d\u0442\u043e \u043d\u0435 \u0434\u0430\u0451\u0442 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0443 \u043f\u0435\u0440\u0435\u0444\u0438\u043b\u044c\u0442\u0440\u043e\u0432\u0430\u0442\u044c \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0435. \u041a\u043e\u0434 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u0421\u0438 \u0441 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u044f\u043c\u0438 \u0434\u043b\u044f SSE2, AVX2 \u0438 ARM Neon. \u0422\u0430\u043a\u0436\u0435 \u0434\u043e\u0441\u0442\u0443\u043f\u043d\u0430 WebAssembly-\u0432\u0435\u0440\u0441\u0438\u044f, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0430\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":41843,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-41842","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Nou proiect pentru eliminarea artefactelor din JPEG | ProHoster","description":"Proiectul JPEG Quant Smooth a fost publicat pe GitHub, destinat s\u0103 elimine artefactele de compresie din imaginile 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