{"id":485,"date":"2017-05-19T16:21:35","date_gmt":"2017-05-19T07:21:35","guid":{"rendered":"http:\/\/msiplab.eng.niigata-u.ac.jp\/?page_id=485"},"modified":"2026-01-01T05:39:20","modified_gmt":"2025-12-31T20:39:20","slug":"imagetransform","status":"publish","type":"page","link":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/projects\/imagetransform","title":{"rendered":"\u753b\u50cf\u5909\u63db"},"content":{"rendered":"<p><\/p>\n<h1>\u5c40\u6240\u69cb\u9020\u5316\u30e6\u30cb\u30bf\u30ea\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3068\u975e\u5206\u96e2\u91cd\u8907\u5909\u63db<\/h1>\n<ul>\n<li><a href=\"https:\/\/www.niigata-u.ac.jp\/wp-content\/uploads\/2022\/07\/kakenhi_news_no7.pdf\">\u65b0\u6f5f\u5927\u5b66\u79d1\u7814\u8cbb\u30cb\u30e5\u30fc\u30b9 vol.7<\/a><\/li>\n<li><a href=\"https:\/\/www.niigata-u.ac.jp\/wp-content\/uploads\/2021\/08\/kakenhi_news02_fix.pdf\">\u65b0\u6f5f\u5927\u5b66\u79d1\u7814\u8cbb\u30cb\u30e5\u30fc\u30b9 vol.2<\/a><\/li>\n<\/ul>\n<h2>\u672c\u7814\u7a76\u306e\u6982\u8981<\/h2>\n<p>\u753b\u50cf\u5909\u63db\u6280\u8853\u306fJPEG, JPEG2000\u3001MPEG\u306a\u3069\u306e\u5727\u7e2e\u7b26\u53f7\u5316\uff0c\u30ce\u30a4\u30ba\u9664\u53bb\u3084\u8d85\u89e3\u50cf\u306a\u3069\u306e\u753b\u50cf\u5fa9\u5143\u3001\u753b\u50cf\u8a8d\u8b58\u305f\u3081\u306e\u7279\u5fb4\u62bd\u51fa\u306a\u3069\u306b\u5f79\u7acb\u3064\u8981\u7d20\u6280\u8853\u3067\u3059\u3002\u4ee3\u8868\u4f8b\u3068\u3057\u3066\u3001\u96e2\u6563\u30b3\u30b5\u30a4\u30f3\u5909\u63db\uff08DCT\uff09\u3084\u96e2\u6563\u30a6\u30a7\u30fc\u30d6\u30ec\u30c3\u30c8\u5909\u63db\uff08DWT\uff09\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002<\/p>\n<p>\u4ee5\u4e0b\u3067\u306fMSIP Lab \u72ec\u81ea\u306e\u63d0\u6848\u3067\u3042\u308b<\/p>\n<ul>\n<li>\u5c40\u6240\u69cb\u9020\u5316\u30e6\u30cb\u30bf\u30ea\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/li>\n<li>\u975e\u5206\u96e2\u5197\u9577\u91cd\u8907\u5909\u63db<\/li>\n<li>\u975e\u5206\u96e2\u91cd\u8907\u76f4\u4ea4\u5909\u63db<\/li>\n<\/ul>\n<p>\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<p>\u89e3\u8aac\u8a18\u4e8b\u3082\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n<ul>\n<li><a href=\"https:\/\/doi.org\/10.1587\/essfr.17.2_116\">\u30d5\u30a3\u30eb\u30bf\u30d0\u30f3\u30af\u7406\u8ad6\u306b\u57fa\u3065\u304f\u7573\u8fbc\u307f\u8f9e\u66f8\u5b66\u7fd2<\/a>\uff0c\u6751\u677e\u6b63\u543e\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a \u57fa\u790e\u30fb\u5883\u754c\u30bd\u30b5\u30a4\u30a8\u30c6\u30a3 Fundamentals Review, 2023, 17 \u5dfb, 2 \u53f7, p. 116-125<\/li>\n<li><a href=\"https:\/\/www.journal.ieice.org\/summary.php?id=k106_1_2&amp;year=2023&amp;lang=J\">\u753b\u50cf\u5fa9\u5143\u306b\u304a\u3051\u308b\u5206\u6790\u30fb\u5408\u6210\u30b7\u30b9\u30c6\u30e0<\/a>\uff0c\u6751\u677e\u6b63\u543e\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8a8c2023\u5e741\u6708\u53f7<\/li>\n<\/ul>\n<h2>\u5c40\u6240\u69cb\u9020\u5316\u30e6\u30cb\u30bf\u30ea\u30cd\u30c3\u30c8\u30ef\u30fc\u30af(LSUN)<\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-4173\" src=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2024\/05\/perf_eval_setup-300x133.png\" alt=\"\" width=\"300\" height=\"133\" srcset=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2024\/05\/perf_eval_setup-300x133.png 300w, https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2024\/05\/perf_eval_setup.png 720w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>\u975e\u5206\u96e2\u91cd\u8907\u76f4\u4ea4\u5909\u63db\u306b\u5c40\u6240\u53ef\u5909\u69cb\u9020\u3092\u5c0e\u5165\u3057\uff0c\u91cd\u8907\u6027\uff0c\u5c40\u5728\u6027\u3092\u6709\u3059\u308b\u81ea\u5df1\u6559\u5e2b\u3042\u308a\u5b66\u7fd2\u53ef\u80fd\u3067\u7dda\u5f62\u306a\u81ea\u5df1\u7b26\u53f7\u5316\u5668\u306e\u7406\u8ad6\u3092\u4e0e\u3048\u8a2d\u8a08\u624b\u6cd5\u3092\u63d0\u6848\u3057\u307e\u3057\u305f\uff0e<\/p>\n<p>\u63d0\u6848\u6cd5\u3067\u3042\u308b\u5c40\u6240\u69cb\u9020\u5316\u30e6\u30cb\u30bf\u30ea\u30cd\u30c3\u30c8\u30ef\u30fc\u30af(LSUN)\u306f\uff0c\u7406\u8ad6\u4e0a\uff0c\u4efb\u610f\u306e\u6b21\u5143\u306e\u4fe1\u53f7\uff08\u4efb\u610f\u306e\u968e\u6570\u306e\u30c6\u30f3\u30bd\u30eb\uff09\u3092\u5bfe\u8c61\u306b\u3067\u304d\u307e\u3059\uff0e<\/p>\n<p>\u307e\u305f\uff0c\u5c40\u6240\u69cb\u9020\u304b\u3089\u9ad8\u6b21\u5143\u30c7\u30fc\u30bf\u306b\u57cb\u3081\u8fbc\u307e\u308c\u305f\u591a\u69d8\u4f53\u306e\u63a5\u7a7a\u9593\u3092\u6349\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\uff0e<\/p>\n<p>\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u5168\u4f53\u306e\u76f4\u4ea4\u6027\u304b\u3089\u7b26\u53f7\u5316\u5668\u304b\u3089\u968f\u4f34\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3068\u3057\u3066\u7c21\u4fbf\u306b\u5fa9\u53f7\u5668\u3092\u4e0e\u3048\uff0c\u76f4\u6d41\u7121\u6f0f\u6d29\u6761\u4ef6\uff08\u30a6\u30a7\u30fc\u30d6\u30ec\u30c3\u30c8\u5909\u63db\u3067\u3044\u3046\u30a2\u30c9\u30df\u30c3\u30b7\u30d6\u30eb\u6761\u4ef6\uff09\u3092\u69cb\u9020\u7684\u306b\u4fdd\u8a3c\u3059\u308b\u305f\u3081\uff0c\u968e\u5c64\u5316\u306b\u3082\u9069\u3057\u3066\u3044\u307e\u3059\u3002\u69cb\u9020\u7684\u306b\u6b21\u5143\u524a\u6e1b\u306b\u5229\u7528\u3067\u304d\uff0c\u63a8\u8ad6\u6642\u306b\u306f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u3088\u3046\u306a\u975e\u7dda\u5f62\u95a2\u6570\u3068\u306e\u7d44\u307f\u5408\u308f\u305b\u305f\u6df1\u5c64\u69cb\u9020\u3084\u30b9\u30d1\u30fc\u30b9\u6700\u9069\u5316\u554f\u984c\u306e\u3088\u3046\u306a\u7e70\u308a\u8fd4\u3057\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u4e0d\u8981\u3067\u3059\uff0e\u3082\u3061\u308d\u3093\uff0c\u7dda\u5f62\u5c64\u3068\u3057\u3066\u7d44\u307f\u8fbc\u307f\u3093\u3060\u4f75\u7528\u3082\u53ef\u80fd\u3067\u3059\uff0e<\/p>\n<p>\u4e8b\u4f8b\u306b\u57fa\u3065\u304f\u8a2d\u8a08\u304c\u53ef\u80fd\u3067\uff0c\u4e3b\u6210\u5206\u5206\u6790(PCA)\u3084\u56fa\u6709\u76f4\u4ea4\u5206\u89e3(POD)\u306e\u4ee3\u308f\u308a\u3042\u308b\u3044\u306f\u524d\u51e6\u7406\u3068\u3057\u3066\u5229\u7528\u3059\u308b\u3053\u3068\u3067\u9ad8\u6b21\u5143\u30c7\u30fc\u30bf\u3092\u3088\u308a\u4f4e\u6b21\u5143\u306e\u7279\u5fb4\u7a7a\u9593\u306b\u5199\u50cf\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\uff0e<\/p>\n<p>\u91cd\u8907\u69cb\u9020\u3084\u968e\u5c64\u69cb\u9020\u306e\u5c0e\u5165\u306e\u5bb9\u6613\u3055\u304c\u3053\u306e\u7d50\u679c\u306e\u4e3b\u306a\u8981\u56e0\u3068\u3044\u3048\u307e\u3059\uff0e<\/p>\n<p>\u30c7\u30fc\u30bf\u99c6\u52d5\u306b\u3088\u308b\u30e2\u30c7\u30ea\u30f3\u30b0\u624b\u6cd5\u306e\u666e\u53ca\u306b\u3088\u308a\uff0c\u9632\u707d\u5fdc\u7528\u306a\u3069\u8907\u96d1\u306a\u7269\u7406\u73fe\u8c61\u306e\u89e3\u660e\u3078\u306e\u671f\u5f85\u304c\u9ad8\u307e\u3063\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u30b5\u30a4\u30d0\u30fc\u30fb\u30d5\u30a3\u30b8\u30ab\u30eb\u30fb\u30b7\u30b9\u30c6\u30e0(CPS)\u5b9f\u73fe\u306e\u305f\u3081\u306e\u30c7\u30b8\u30bf\u30eb\u30c4\u30a4\u30f3\u306e\u8a2d\u8a08\u306a\u3069\u30c7\u30fc\u30bf\u99c6\u52d5\u306b\u3088\u308b\u30e2\u30c7\u30ea\u30f3\u30b0\u624b\u6cd5\u306e\u91cd\u8981\u5ea6\u304c\u5897\u3057\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u6df1\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3068\u306e\u76f8\u6027\u3082\u826f\u304f\uff0c\u7573\u307f\u8fbc\u307f\u5c64\u306b\u4ee3\u308f\u308b\u65b0\u305f\u306a\u7dda\u5f62\u5c64\u3068\u3057\u3066\u671f\u5f85\u3055\u308c\u307e\u3059\uff0e\u307e\u305f\uff0c\u30b9\u30d1\u30fc\u30b9\u30e2\u30c7\u30ea\u30f3\u30b0\u306e\u67a0\u7d44\u307f\u306b\u7d44\u307f\u8fbc\u3080\u3053\u3068\u3067\uff0c\u65e2\u5b58\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u767a\u5c55\u306b\u3082\u671f\u5f85\u3055\u308c\u307e\u3059\uff0e<\/p>\n<h3>MATLAB\/PyTorch\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9<\/h3>\n<ul>\n<li><a href=\"https:\/\/github.com\/msiplab\/TanSacNet\">TanSacNet<\/a><\/li>\n<\/ul>\n<h3><span style=\"font-size: 1.125rem;\">\u7814\u7a76\u6210\u679c<\/span><\/h3>\n<h4>\u5b66\u8853\u8ad6\u6587<\/h4>\n<ul class=\"list1\">\n<li>Yasas GODAGE, Eisuke KOBAYASHI, Shogo MURAMATSU, \u201c<strong>Locally-Structured Unitary Network,<\/strong>\u201c<em>\u00a0APSIPA Transactions on Signal and Information Processing,\u00a0<a href=\"https:\/\/nowpublishers.com\/article\/Details\/SIP-2024-0008\">https:\/\/nowpublishers.com\/article\/Details\/SIP-2024-0008<\/a>,<\/em>\u00a0\u00a0May 2024<br \/>\n(<a href=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2026\/01\/LSUN_Poster.pdf\">Poster PDF<\/a>)<\/li>\n<\/ul>\n<h4>\u56fd\u969b\u4f1a\u8b70<\/h4>\n<ul>\n<li>Godage Yasas, Shogo Muramatsu:\u00a0<strong data-bind=\"text: title\">Tangent Space Sampling of Video Sequence with Locally Structured Unitary Network,<\/strong><em>\u00a0Proc. of 2023 IEEE\u3000International Conference on Visual Communications and Image Processing<\/em>,\u00a0<a href=\"https:\/\/doi.org\/10.1109\/VCIP59821.2023.10402611\">DOI:10.1109\/VCIP59821.2023.10402611<\/a>, Dec. 2023<\/li>\n<\/ul>\n<h2>\u8b1d\u8f9e<\/h2>\n<p>\u672c\u7814\u7a76\u6210\u679c\u306f\uff0c\u79d1\u7814\u8cbb\u57fa\u76e4\u7814\u7a76(A) ( 22H00512)\u306e\u88dc\u52a9\u306b\u3088\u308b\uff0e<\/p>\n<h2><\/h2>\n<h2>\u975e\u5206\u96e2\u5197\u9577\u91cd\u8907\u5909\u63db(NSOLT)<\/h2>\n<h3><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-884 size-full\" src=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2017\/07\/latstrnsolt.png\" alt=\"\" width=\"720\" height=\"426\" srcset=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2017\/07\/latstrnsolt.png 720w, https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/wordpress\/wp-content\/uploads\/2017\/07\/latstrnsolt-300x178.png 300w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \/><\/h3>\n<p>\u975e\u5206\u96e2\u91cd\u8907\u76f4\u4ea4\u5909\u63db\u3092\u5197\u9577\u5909\u63db\u306b\u62e1\u5f35\u3057\uff0c\u91cd\u8907\u6027\uff0c\u5bfe\u79f0\u6027\uff0c\u5c40\u5728\u6027\u3092\u6709\u3059\u308b\u5197\u9577\u5909\u63db\u306e\u7406\u8ad6\u3092\u4e0e\u3048\u8a2d\u8a08\u624b\u6cd5\u3092\u63d0\u6848\u3057\u307e\u3057\u305f\uff0e<\/p>\n<p>\u63d0\u6848\u6cd5\u3067\u3042\u308b\u975e\u5206\u96e2\u5197\u9577\u91cd\u8907\u5909\u63db\uff08NSOLT\uff09\u306f\uff0c\u7406\u8ad6\u4e0a\uff0c\u4efb\u610f\u306e\u6b21\u5143\u306e\u4fe1\u53f7\uff08\u4efb\u610f\u306e\u968e\u6570\u306e\u30c6\u30f3\u30bd\u30eb\uff09\u3092\u5bfe\u8c61\u306b\u3067\u304d\u307e\u3059\uff0e<\/p>\n<p>\u307e\u305f\uff0c\u5197\u9577\u5ea6\u3082\u4efb\u610f\u306e\u6709\u7406\u6570\u306b\u8a2d\u5b9a\u3067\u304d\u308b\u5229\u70b9\u3092\u6301\u3061\u307e\u3059\uff0e<\/p>\n<p>\u5197\u9577\u5ea6\u306f\u30e1\u30e2\u30ea\u6d88\u8cbb\u91cf\u306b\u76f4\u63a5\u5f71\u97ff\u3059\u308b\u305f\u3081\uff0c\u305d\u306e\u9ad8\u3044\u81ea\u7531\u5ea6\u306f\u5927\u5bb9\u91cf\u30dc\u30ea\u30e5\u30fc\u30e0\u30c7\u30fc\u30bf\u306e\u51e6\u7406\u3084\u30e1\u30e2\u30ea\u8cc7\u6e90\u306e\u9650\u3089\u308c\u308b\u7d44\u8fbc\u307f\u5b9f\u88c5\u306a\u3069\u3067\u52b9\u679c\u3092\u767a\u63ee\u3057\u307e\u3059\uff0e<\/p>\n<p>\u3055\u3089\u306b\uff0c\u30d1\u30e9\u30e6\u30cb\u30bf\u30ea\u6027\u3092\u6e80\u305f\u3059\u30d5\u30a3\u30eb\u30bf\u30d0\u30f3\u30af\uff08\u30d1\u30fc\u30bb\u30d0\u30eb\u30bf\u30a4\u30c8\u6027\u3092\u6e80\u305f\u3059\u8f9e\u66f8\uff09\u306e\u8a2d\u8a08\u3082\u5bb9\u6613\u3067\uff0c\u591a\u304f\u306e\u30b9\u30d1\u30fc\u30b9\u6700\u9069\u5316\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3068\u7c21\u4fbf\u306b\u4f75\u7528\u3067\u304d\u307e\u3059\uff0e<\/p>\n<p>\u4e8b\u4f8b\u306b\u57fa\u3065\u304f\u8a2d\u8a08\u304c\u53ef\u80fd\u3067\uff0c\u65e2\u5b58\u6cd5\u306e\u4e00\u3064\u3067\u3042\u308b\u30b9\u30d1\u30fc\u30b9K-SVD\u3088\u308a\u3082\u9ad8\u3044\u30b9\u30d1\u30fc\u30b9\u8fd1\u4f3c\u6027\u80fd\u3092\u793a\u3057\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u91cd\u8907\u69cb\u9020\u3084\u968e\u5c64\u69cb\u9020\u306e\u5c0e\u5165\u306e\u5bb9\u6613\u3055\u304c\u3053\u306e\u7d50\u679c\u306e\u4e3b\u306a\u8981\u56e0\u3068\u3044\u3048\u307e\u3059\uff0e<\/p>\n<p>IoT\u306e\u666e\u53ca\u306b\u3088\u308a\u52a3\u60aa\u306a\u74b0\u5883\u306b\u304a\u3044\u3066\u30bb\u30f3\u30b7\u30f3\u30b0\u3055\u308c\u308b\u753b\u50cf\u3084\u6620\u50cf\u306e\u307b\u304b\uff0cICT\u306e\u533b\u7642\u5206\u91ce\u3078\u306e\u5c55\u958b\u306b\u3088\u308a\u6975\u9650\u72b6\u614b\u3067\u53d6\u5f97\u3055\u308c\u308b\u30dc\u30ea\u30e5\u30fc\u30e0\u30c7\u30fc\u30bf\u306e\u5897\u52a0\u304c\u898b\u8fbc\u307e\u308c\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u3053\u306e\u7d50\u679c\uff0c\u753b\u50cf\u304a\u3088\u3073\u30dc\u30ea\u30e5\u30fc\u30e0\u30c7\u30fc\u30bf\u5fa9\u5143\u6280\u8853\u306e\u5f79\u5272\u306f\u91cd\u8981\u5ea6\u3092\u5897\u3057\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u8a8d\u8b58\u5206\u91ce\u3067\u6210\u529f\u3057\u3066\u3044\u308b\u7573\u8fbc\u307f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af(CNN)\u3068\u30d5\u30a3\u30eb\u30bf\u30d0\u30f3\u30af\u306e\u985e\u4f3c\u6027\u304b\u3089\uff0c\u8a8d\u8b58\u5206\u91ce\u3078\u306e\u5c55\u958b\u3082\u671f\u5f85\u3067\u304d\u307e\u3059\uff0e<\/p>\n<h3>MATLAB \u30bd\u30fc\u30b9\u30b3\u30fc\u30c9<\/h3>\n<ul>\n<li><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/45084-saivdr-package\">SaivDr Package<\/a><\/li>\n<\/ul>\n<h3>\u7814\u7a76\u6210\u679c<\/h3>\n<h4>\u5b66\u8853\u8ad6\u6587<\/h4>\n<ul class=\"list1\">\n<li>Shogo Muramatsu, Kosuke Furuya and Naotaka Yuki, <strong>Multidimensional Nonseparable Oversampled Lapped Transforms: Theory and Design<\/strong>\uff0c<em>IEEE Trans. on Signal Process.\uff0c<\/em><span class=\"ng-binding ng-scope\">Vol.\u00a065<\/span><em><span class=\"ng-scope\">, <\/span><\/em><span class=\"ng-scope\">No. 5<\/span><em><span class=\"ng-scope\"><span class=\"ng-binding ng-scope\">, <\/span><\/span>\u00a0<\/em>pp.1251 <span class=\"ng-binding ng-scope\">-1264<\/span><em>, <\/em>DOI:<em> \u00a0<\/em><a href=\"http:\/\/dx.doi.org\/10.1109\/TSP.2016.2633240\">10.1109\/TSP.2016.2633240<\/a>,\u00a0Mar. 2017.<\/li>\n<li>Kosuke Furuya, Shintaro Hara, Kenta Seino and Shogo Muramatsu,\u00a0<strong>Boundary Operation of 2-D Non-separable Oversampled Lapped transforms, \u00a0<\/strong><em>APSIPA Transactions on Signal and Information Processing,<\/em>\u00a0Vol. 5, pp.1-9, DOI:<a class=\"cboDOI\" href=\"http:\/\/dx.doi.org\/10.1017\/ATSIP.2016.3\" target=\"_blank\" rel=\"noopener noreferrer\">10.1017\/ATSIP.2016.3<\/a>,\u00a0April 2016.<\/li>\n<\/ul>\n<h4>\u56fd\u969b\u4f1a\u8b70<\/h4>\n<ul>\n<li>Shogo Muramatsu, Masaki Ishii and Zhiyu Chen, <strong>Efficient Parameter Optimization for Example-Based Design of\u00a0Non-separable Oversampled Lapped Transform<\/strong>, <em>Proc. of 2016 IEEE Intl.\u00a0Conf. on Image Processing (ICIP)<\/em>, Sept. 2016.<\/li>\n<li>Shogo Muramatsu, <strong>Structured Dictionary Learning with 2-D Non-separable Oversampled Lapped Transform<\/strong>, <em>Proc. of 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, pp.2643-2647, May 2014<\/li>\n<li>Kousuke Furuya, Shintaro Hara and Shogo Muramatsu, <strong>Boundary Operation of 2-D non-separable Oversampled Lapped Transforms<\/strong>, <em>Proc. of Asia Pacific Signal and Information Proc. Assoc. Annual Summit and Conf. (APSIPA ASC)<\/em>, Kaohsiung, Taiwan, Nov. 2013<\/li>\n<li>Shogo Muramatsu and Natsuki Aizawa, <strong>Image Restoration with 2-D Non-separable Oversampled Lapped Transforms<\/strong>, <em>Proc. of 2013 IEEE International Conference on Image Processing(ICIP)<\/em>, Sep. 2013<\/li>\n<li>Shogo Muramatsu and Natsuki Aizawa, <strong>Lattice Structures for 2-D Non-separable Oversampled Lapped Transforms<\/strong>, <em>Proc. of 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, May 2013<\/li>\n<\/ul>\n<h2>\u5de5\u696d\u6240\u6709\u6a29<\/h2>\n<ul>\n<li>\u7279\u8a31\uff0c\u753b\u50cf\u5909\u63db\u88c5\u7f6e\u3001\u753b\u50cf\u5909\u63db\u65b9\u6cd5\u3001\u53ca\u3073\u753b\u50cf\u5909\u63db\u30d7\u30ed\u30b0\u30e9\u30e0\uff0c\u6751\u677e\u3000\u6b63\u543e<br \/>\n\u767b\u9332\u756a\u53f7\uff08 \u7279\u8a31\u7b2c6066280\u53f7\uff0c2017\u5e7401\u670806\u65e5 \uff09 \uff0c\u65e5\u672c\u56fd<\/li>\n<\/ul>\n<h2>\u8b1d\u8f9e<\/h2>\n<p>\u672c\u7814\u7a76\u6210\u679c\u306f\uff0c\u79d1\u7814\u8cbb\u57fa\u76e4\u7814\u7a76(B) (19H04135)\u306e\u88dc\u52a9\u306b\u3088\u308b\uff0e<\/p>\n<h2>\u975e\u5206\u96e2\u91cd\u8907\u76f4\u4ea4\u5909\u63db<\/h2>\n<p>\u30d6\u30ed\u30c3\u30af\u9593\u306e\u95a2\u4fc2\u3092\u5229\u7528\u3059\u308b\u91cd\u8907\u76f4\u4ea4\u5909\u63db\uff08LOT\uff09\u3092\u591a\u6b21\u5143\u975e\u5206\u96e2\u30b7\u30b9\u30c6\u30e0\u306b\u62e1\u5f35\u3057\u307e\u3057\u305f\uff0e<\/p>\n<p>\u3055\u3089\u306b\uff0c\u753b\u50cf\u4e2d\u306b\u542b\u307e\u308c\u308b\u4efb\u610f\u306e\u65b9\u5411\u306b\u50be\u659c\u3057\u305f\u4e00\u6b21\u5e73\u9762\u6210\u5206\u3092\u6d88\u5931\u3055\u305b\u308b\u30d5\u30a3\u30eb\u30bf\u306e\u6027\u8cea\u3068\u3057\u3066\u50be\u659c\u30d0\u30cb\u30c3\u30b7\u30f3\u30b0\u30e2\u30fc\u30e1\u30f3\u30c8(TVM)\u3092\u5b9a\u7fa9\u3057\uff0c\u305d\u306e\u7406\u8ad6\u306e\u69cb\u7bc9\u3068\u540c\u7406\u8ad6\u306b\u57fa\u3065\u304f\u6307\u5411\u6027\u91cd\u8907\u76f4\u4ea4\u5909\u63db(DirLOT)\u306e\u8a2d\u8a08\u6cd5\u3092\u63d0\u6848\u3057\u307e\u3057\u305f\uff0e<\/p>\n<p>\u3053\u306e\u7406\u8ad6\u306f\u4e00\u6b21\u5143\u306e\u5206\u6790\uff0f\u5408\u6210\u30b7\u30b9\u30c6\u30e0\u306b\u306f\u73fe\u308c\u306a\u3044\u6982\u5ff5\u3067\uff0c\u591a\u6b21\u5143\u30b7\u30b9\u30c6\u30e0\u306e\u7279\u5fb4\u3092\u6d3b\u304b\u3057\u305f\u72ec\u5275\u6027\u3092\u6709\u3057\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u6c4e\u7528\u7684\u306a\u7406\u8ad6\u3092\u793a\u3059\u307b\u304b\uff0cTVM\u6761\u4ef6\u3092\u6e80\u305f\u3059\u5206\u6790\uff0f\u5408\u6210\u30b7\u30b9\u30c6\u30e0\u306e\u8a2d\u8a08\u624b\u6cd5\u3092\u78ba\u7acb\u3057\uff0c\u53ef\u5206\u96e2\u30b7\u30b9\u30c6\u30e0\u3067\u306f\u306a\u3057\u3048\u306a\u3044\u6307\u5411\u6027\u3092\u6709\u3059\u308b2\u00d72\u5206\u5272\u306e\u5bfe\u79f0\u6b63\u898f\u76f4\u4ea4\u30a6\u30a7\u30fc\u30d6\u30ec\u30c3\u30c8\u5909\u63db\u3082\u5b9f\u73fe\u3057\u3066\u3044\u307e\u3059\uff0e<\/p>\n<p>\u8907\u6570\u306e\u7570\u306a\u308bDirLOT\u3067\u6df7\u6210\u5909\u63db\u3092\u69cb\u6210\u3057\uff0c\u753b\u50cf\u30ce\u30a4\u30ba\u9664\u53bb\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306b\u3088\u308a\u63d0\u6848\u6cd5\u306e\u6709\u52b9\u6027\u3092\u78ba\u8a8d\u3057\u307e\u3057\u305f\uff0e<\/p>\n<p>IoT\u306e\u666e\u53ca\u306b\u3088\u308a\u52a3\u60aa\u306a\u74b0\u5883\u306b\u304a\u3044\u3066\u30bb\u30f3\u30b7\u30f3\u30b0\u3055\u308c\u308b\u753b\u50cf\u3084\u6620\u50cf\u306e\u5897\u52a0\u304c\u898b\u8fbc\u307e\u308c\u308b\u4e2d\uff0c\u753b\u50cf\u5fa9\u5143\u6280\u8853\u306e\u5f79\u5272\u306f\u91cd\u8981\u5ea6\u3092\u5897\u3057\uff0c\u753b\u50cf\u3092\u30b9\u30d1\u30fc\u30b9\u306b\u8868\u73fe\u3067\u304d\u308b\u5197\u9577\u5909\u63db\u306b\u5bc4\u305b\u3089\u308c\u308b\u671f\u5f85\u3082\u5927\u304d\u304f\u306a\u3063\u3066\u3044\u307e\u3059\uff0e<\/p>\n<h3>MATLAB \u30bd\u30fc\u30b9\u30b3\u30fc\u30c9<\/h3>\n<ul>\n<li><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/32603\">DirLOT Toolbox<\/a><\/li>\n<li><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/45084-saivdr-package\">SaivDr Package<\/a><\/li>\n<\/ul>\n<h3>\u7814\u7a76\u6210\u679c<\/h3>\n<h4>\u5b66\u8853\u8ad6\u6587<\/h4>\n<ul>\n<li>Chen Zhiyu and Shogo Muramatsu, <strong>Multi-focus Image Fusion based on Multiple Directional LOTs<\/strong>, <em>IEICE Trans. on Fundamentals<\/em>, vol.E98-A, no.11,\u00a0<span class=\"TEXT-BODY\">pp.<\/span><span class=\"TEXT-BODY\">2360-2365,\u00a0<\/span>Nov. 2015.<\/li>\n<li>Chen Zhiyu and Shogo Muramatsu, <strong>SURE-LET Poisson Denoising with Multiple Directional LOTs<\/strong>, <em>IEICE Trans. on Fundamentals<\/em>, vol.E98-A, no.8, pp. 1820-1828, Aug. 2015.<\/li>\n<li>Natsuki Aizawa, Shogo Muramatsu and Masahiro Yukawa, <strong>Image Restoration with Multiple DirLOTs<\/strong>, <em>IEICE Trans. on Fundamentals<\/em>, Vol.E96-A,No.10,pp.1954-1961,DOI: <a href=\"http:\/\/search.ieice.org\/bin\/summary.php?id=e96-a_10_1954\" rel=\"nofollow\">10.1587\/transfun.E96.A.1954<\/a>, Oct. 2013.<\/li>\n<li>Shogo Muramatsu, Dandan Han, Tomoya Kobayashi and Hisakazu Kikuchi: <strong>Directional Lapped Orthogonal Transform: Theory and Design<\/strong>,\u00a0<em>IEEE Trans. on Image Processing<\/em>, Vol.21, No.5, pp.2434-2448, DOI: <a href=\"http:\/\/dx.doi.org\/10.1109\/TIP.2011.2182055\">10.1109\/TIP.2011.2182055<\/a>, May 2012.<\/li>\n<li>Shogo Muramatsu, Tomoya Kobayashi, Minoru Hiki and Hisakazu Kikuchi: <strong>Boundary Operation of 2-D Non-separable Linear-phase Paraunitary Filter Banks<\/strong>,\u00a0<em>IEEE Trans. on Image Processing<\/em>, Vol.21, No.4, pp.2314-2318, DOI: <a href=\"http:\/\/dx.doi.org\/10.1109\/TIP.2011.2181527\">10.1109\/TIP.2011.2181527<\/a>, April 2012.<\/li>\n<li>Atsuyuki Adachi, Shogo Muramatsu, Hisakazu Kikuchi, <strong>Constraints of Second-Order Vanishing Moments on Lattice Structures for Non-separable Orthogonal Symmetric Wavelets<\/strong>, <em>IEICE Trans. on Fundamentals<\/em>, Vol. E92-A, No. 3, pp.788-797, Mar. 2009. (<a href=\"http:\/\/search.ieice.org\/bin\/summary.php?id=e92-a_3_788&amp;category=A&amp;year=2009&amp;lang=E&amp;abst=\">Summary<\/a>)<\/li>\n<li>Shogo Muramatsu, Akihiko Yamada and Hitoshi Kiya, <strong>A\u00a0Design Method of Multidimensional Linear-phase Paraunitary Filter Banks with a Lattice Structure,<\/strong><em> I<\/em><em>EEE Transactions on Signal Processing<\/em>, vol. 47, no. 3, pp. 690-700, DOI:\u00a0<a href=\"https:\/\/doi.org\/10.1109\/78.747776\">10.1109\/78.747776<\/a>,\u00a0Mar. 1999.<\/li>\n<\/ul>\n<h4>\u56fd\u969b\u4f1a\u8b70<\/h4>\n<ul>\n<li>Zhiyu Chen and Shogo Muramatsu, <strong>Poisson denoising with multiple Directional LOTs<\/strong>, <em>Proc. of 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, pp.1234-1238, May 2014.<\/li>\n<li>Natsuki Aizawa and Shogo Muramatsu, <strong>FISTA-Based Image Restoration with Multiple DirLOTs<\/strong>, <em>Proc. of IWAIT 2013<\/em>, Jan. 2013.<\/li>\n<li>Shogo Muramatsu, Natsuki Aizawa and Masahiro Yukawa, <strong>Image Restoration with Union of Directional Orthonormal DWTs<\/strong>, <em>Proc. of APSIPA ASC 2012<\/em>, Dec. 2012.<\/li>\n<li>Shogo Muramatsu: <strong>SURE-LET Image Denoising with Multiple Directional LOTs<\/strong>, <em>Proc. of 2012 Picture Coding Symposium (PCS2012)<\/em>, May 2012.<\/li>\n<li>Shogo Muramatsu and Dandan Han: <strong>Image Denoising with Union of Directional Orthonormal DWTs<\/strong>,\u00a0<em>IEEE Proc. of 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, pp.1089-1092, Mar. 2012.<\/li>\n<li>Shogo Muramatsu, Dandan Han and Hisakazu Kikuchi, &#8221;<strong>SURE-LET Image Denoising with Directional LOTs<\/strong>, <em>Proc. of APSIPA ASC 2011<\/em>, Thu-PM.PS1.9, Xi&#8217;an, China, Oct. 18 &#8211; 21, 2011.<\/li>\n<li>Shogo Muramatsu, Tomoya Kobayashi, Dandan Han and Hisakazu Kikuchi, <strong>Design Method of Directional GenLOT with Trend Vanishing Moments<\/strong>, <em>Proc. of APSIPA ASC 2010<\/em>, pp.692-701, Biopolis, Singapore, Dec. 14 &#8211; 17, 2010,<\/li>\n<li>Shogo Muramatsu, Dandan Han, Tomoya Kobayashi and Hisakazu Kikuchi, <strong>Theoretical Analysis of Trend Vanishing Moments for Directional Orthogonal Transforms<\/strong>, <em>Proc. of PCS2010<\/em>, pp.130-133, Nagoya, Japan, Dec. 7-9, 2010.<\/li>\n<li>Tomoya Kobayashi, Shogo Muramatsu and Hisakazu Kikuchi, <strong>2-D Nonseparable GenLOT with Trend Vanishing Moments<\/strong>, <em>IEEE Proc. of International Conf. on Image Proc. (ICIP2010)<\/em>, Hong Kong, pp.385-388, Sep. 2010.<\/li>\n<li>Tomoya Kobayashi, Shogo Muramatsu, Hisakazu Kikuchi, <strong>Two-Degree Vanishing Moments on 2-D Non-separable GenLOT<\/strong>, <em>IEEE Proc. of 2009 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS2009)<\/em>, pp.248-251, Kanazawa, Japan, Dec. 7-9, 2009.<\/li>\n<li>Shogo Muramatsu and Minoru Hiki, <strong>Block-Wise Implementation of Directional GenLOT<\/strong>&#8216;, <em>IEEE Proc. of International Conference on Image Processing (ICIP2009)<\/em>, pp.3977-3980, Cairo, Egypt, Nov. 7-11 2009.<\/li>\n<\/ul>\n<h2>\u8b1d\u8f9e<\/h2>\n<p>\u672c\u7814\u7a76\u6210\u679c\u306f\uff0c\u79d1\u7814\u8cbb\u57fa\u76e4\u7814\u7a76(C) (23560443, 26420347)\u306e\u88dc\u52a9\u306b\u3088\u308b\uff0e<\/p>\n<h2>\u95a2\u9023\u7814\u7a76<\/h2>\n<ul>\n<li><a href=\"http:\/\/code.soundsoftware.ac.uk\/projects\/smallbox\">Dictionary leraning software SMALLbox<\/a><\/li>\n<li><a href=\"http:\/\/www.curvelet.org\/software.html Waveatom:http:\/\/waveatom.org\/\">Curvelet Transforms<\/a><\/li>\n<li><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/8837\">Contourlet toolbox<\/a><\/li>\n<li><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/10049\">Nonsubsampled Contourlet Toolbox<\/a><\/li>\n<li><a href=\"http:\/\/www.ux.uis.no\/~karlsk\/ICTools\/ictools.html\">Image Compression Tools for MATLAB<\/a><\/li>\n<li><a href=\"http:\/\/thames.cs.rhul.ac.uk\/~fionn\/Sparse_Signal_Recipes\/Sparse_Signal_Recipes.html\">Sparse Singal Recipes<\/a><\/li>\n<li><a href=\"http:\/\/www.springer.com\/mathematics\/analysis\/book\/978-1-4419-7010-7\">Sparse and Redundant Representation<\/a><\/li>\n<li><a href=\"http:\/\/www.cipr.rpi.edu\/research\/SPIHT\/spiht0.html\">SPHIT Image Compression<\/a><\/li>\n<li><a href=\"http:\/\/www.ux.uis.no\/~karlsk\/dle\/index.html\">Dictionary Learning Tools for MATLAB<\/a><\/li>\n<li><a href=\"http:\/\/www.cmap.polytechnique.fr\/scattering\/\">Scattering Operators<\/a><\/li>\n<\/ul>\n<h2>\u30ea\u30f3\u30af<\/h2>\n<ul>\n<li><a href=\"http:\/\/www.fourierandwavelets.org\">Fourier and Wavelet Signal Processing<\/a><\/li>\n<li><a href=\"http:\/\/lcav.epfl.ch\/reproducible_research\">Reproducible Research<\/a><\/li>\n<li><a href=\"http:\/\/sipi.usc.edu\/database\/\">The USC-SIPI Image Database<\/a><\/li>\n<\/ul>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>\u5c40\u6240\u69cb\u9020\u5316\u30e6\u30cb\u30bf\u30ea\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3068\u975e\u5206\u96e2\u91cd\u8907\u5909\u63db \u65b0\u6f5f\u5927\u5b66\u79d1\u7814\u8cbb\u30cb\u30e5\u30fc\u30b9 vol.7 \u65b0\u6f5f\u5927\u5b66\u79d1\u7814\u8cbb\u30cb\u30e5\u30fc\u30b9 vol.2 \u672c\u7814\u7a76\u306e\u6982\u8981 \u753b\u50cf\u5909\u63db\u6280\u8853\u306fJPEG, JPEG2000\u3001MPEG\u306a\u3069\u306e\u5727\u7e2e\u7b26\u53f7\u5316\uff0c\u30ce\u30a4\u30ba\u9664\u53bb\u3084\u8d85\u89e3 &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/projects\/imagetransform\" class=\"more-link\"><span class=\"screen-reader-text\">&#8220;\u753b\u50cf\u5909\u63db&#8221; \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":1,"featured_media":4173,"parent":17,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-485","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/pages\/485","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/comments?post=485"}],"version-history":[{"count":93,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/pages\/485\/revisions"}],"predecessor-version":[{"id":5026,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/pages\/485\/revisions\/5026"}],"up":[{"embeddable":true,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/pages\/17"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/media\/4173"}],"wp:attachment":[{"href":"https:\/\/www.eng.niigata-u.ac.jp\/~msiplab\/index.php\/wp-json\/wp\/v2\/media?parent=485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}