HTML5 Canvas Pixel Interpolation

JavaScript performance comparison

Revision 16 of this test case created by Mario Klingemann

Info

Compare methods to do canvas pixel interpolation / filtering. Compares stuff like nearest-neighbor, bilinear, etc and various optimizations. Please add any optimizations or other interpolation methods to this page.

This version use an Uint32 Array view - the bit shifts still have to be adjusted for the endianess of the system, so this solution will not work entirely correctly yet.

Preparation code

<canvas id="canvas" width="100" height="100"></canvas>
<script>
Benchmark.prototype.setup = function() {
    var im = new Image();
    im.src = 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5zrHZVhtsADsed7KyP8AA1vuL6XMr/4PHrR+lf4w8X7P1BluARm5+RXZY2o7amhtLMezV5fZs9Wn1a6P+H+ms71S2312iNxMLVxcvjiADEHhHCCevm4vM/EOZxS/VZJYzO5S4P0P9nL9D/ATt9Th9z3EaQ7b/wB8YxSLuAXHc4kAfRBPPbc7/pKs1xPkZTWiwGmSIc/ZrA9zo9P/AKlWBjxgWIRH+CGjPn+cynhyc1mmNdJ5ckh9nE2bMay+i30CBexrnVsj2PLRu9K1rpa/1Nv7v/FoXRfrbUajXnU/acd2z1qbXOOzZ7a3UXOLvS+l/hf0P+D9VRxer1PHqit4ex0CIDnR+czVY/1gwfsWVVn4gNNWWC5jQNux4A9auB9Fvv37P+tKvzeGMgJAeB6eRdH4Rz+TGTy+e8kCeKMJ+rh/f9v9yX6T1t3TemZ9DszBYAxj5dpEA+5tNzJ9rnfm/wCk/MVLKw8h7P0FLq6phpgMaQPzm7tq53pXXn4ljbWl2PYPa59IDmEc/pcV/s2u/dZ+i/4FdCfrHi9VcHZFlbL+AWuIY4/yWW/zLv8Ag1RInEj9KI7606+TBilEzxSBEv0R6co/vR/7qDkZOHY14DmkilvH/fVm7bvV/mWz6/Ef8H9D+rtXT5dm1su+jEgeP9VY/wBo/WJ1/pu/j/gIT/clw3WzS9qIlV7v/9TnuiOq+w47HaF1bYJ7rVfmMkVNBLCQDs0/86WDgC5+DQzUVmto0GpWj9pZSQLBFQAJB5KhMbPfwbAnUew7to5WZRV9npk49twsh1YsaSGOpsY+t/ttZfQ7Zs/8zVTrGR1LNIda1sMYK2tY4nbE7vU9VzrXOd9Hf7/oVoHUOuWXuDcf2sAgR2BWZkZNkBrjDfzQFYwwlEiZA4vHdqcxljOMsYlIwu9PltWD0nPfkWWY2PZkBkG91bS8MLp9M2bPob4ctm4GqhrHtLLCAHtI1Bk/5q0P8XIdfi9cZu5biR5kPyCs/qTnfaHtJ4d/q5W4SJvwLnc1EAxJ14osGHzSyam34zq3gOB1IPgBu/ghNK0Om9OyOq3/AGPHIYS0m2130a6x9K1//ff5amlIRiTLYDVpwxylkiIfMSOGu7n9CoNeNNonduFYjTaD9NzvpepYn+swaOiA2EyL2egPMts9Sf5Hpt/6hdhf9V8JuE1/SrS70mSRafbY1o/nGPhvovft3s/wD/8AwRcX9ZG3ZPSabm1OGPUBfXedG2Cw+nHp7t/tbs9+3/SKp95xzwkROtiNS+Z0ochzEecBnQFTy8Q+Wofo/wB55SeY7p2vdPx0Kl6FriNjHOniGk8q/Th2Y7C64BtzuB3aB2UQFmm9KfBr26N/pRvZjvGY8jeZqqfrt/ee793f/o0or+0fmx9t/D0f+pVA3vGjjMKHrt9SYP8APbv/AAPal7evms+8E3L9Ia31f//V5bpuQfsOOA4+2toPb8USzGbkmZIqmd0+5x/O2t/lLBoyj6NdQBDGgb/NX3dXsJayke0dvGEY4yDYRLLEipdFZFDsbeGSPU7O5DZ0/rKkW2PcATu7BGdflZDWsfJrnmAit21thrGvg6Od9Ix/JlWQO7UkaOmzu/Uiy7GybGVts9K67Gqve2do9U34lTX/AJu718qh9f8AUssU+t0irNe0ay46+I8VcGWK+h4tWGBTfQ5xyWt5OS2yvNrv/lPZZRiMY7/uN+i/waF9aTW7qDrKv5pziWR+679Ixv8AZadqfjoixsdWDm4mPolYnCXDIH+65QmEN3U+rUXinp+XZh1Pc11z64BJYHNYPzfU2Nts/Rb/AE/30VnYD6RmJ408VEtpa7Qb3xpPh+87+v8AuJ2Qx4Tx/L4reSxZsmeMcETPKb4a6dJSkf0YvS4XWxkVvazdXVt9Oo2u3XuDW+n+s7Gso/SfuN/R1/mLO65lZF767WsbtbWKnNYAGw3wZ9FrVinMsqc4GJDgWkCNPzhoiv6i2yktLpn8qoR5eIlxw+U93X5jNliZYM+mWAAlwn0/vaJGYrrmttNhO0nc0dv5CpdUrYxvscXCZM8/NPTlehaS8/o3CHM/Io5xquPrOsnd9INH3KUCQlrs1iYmBoerq5L3Shwd3H+E/wC+qw/ax+6sRHc6oMt39v52f+inHcea0VR8v2v/1vP6ce62qr3AMLBpHCt1YllbSa2gucI3O/uSwSPs1P8AUC0anAiE7iIW8ALmjpuWW7nOj+SFOjCtqsbbcNldbg4knXQz/wBJbdREKl1u8CptDY43P7c+1v8A0dyHvSOlbsuHlYSyRJsgeoj+61XdQLLrAHH0rI3beQWztsj973WV/wDEoz8+x1foXe/0mtfXYDILPojVZDLGtbLue63+l/V1grF2a5++wE/Zwdoa12u2x309zvpPrZsUuPMMYqW3Tuu+JcnHNIZYkCc9Jx8v0/8AuGochtTv0nGyfCRMw3/jP0bVCjILnF7zLiZJ8/8AVq2sj6vdOvx/QbupIH6J4c5wY48O2PLtzfb71y7TbTY6q0FltTiyxp7OaYcE3JmGXawB0LJ8IgOVlK6M51qP3Yp80uDpHdVQ50eJ7q064BzLXQ8NILh2I/OC1X9NxWyAwbe3mEo5REUVfFcBnzHuRqpxH2xeesc/uheq4aLes6dikaMCqWY+DS6LHNY6Jh08eKPug92h7JG9OXLj2UIO7+3/AN9Un5Ac7iay8EsEhvnH85t3fupvUqmfb/PT9H8yP6/83/r6qRnqEiGhf//X4PEtAorH8kK/VeIWCzI2VtgGQIE8SET7Xa6sEO2OBkbZkx9NSeli9d7PSV5A01WJ1HJORe506OPHkNG/9FRd1KSG16/vPPAHdVSS9xcJIGg/gmyiAdG1yspcJMhV0B5fpOh0elluexzxLKf0hHYkfzbf89dR9r7zqe64c5ORSH01uNYcYsjkkfm7vpe1Tq6nm1M2NtMaRpxHgmmAO5W5c0jM0BWz2v2rssf6yVMexnUaxFoIrvI/ObxU938qv+a/zFiM6v1Bghthhvu1EwP/ACPuQbM7Msa5tl73sf8ASaXSDBke1IQANgrRll2ptC3c2CtzFy92FSXGSGBp/s+z/vq5ut528IjepW0gVNaC1vE+eqNAnVs8zkMsUSNTf4O8/I81TzrN1O8OI9MhzYid0jUuf7fT/eZ+eqP7VYeWED4hAyc/1WhjW+0GXbu57J3DEdWjxTPRfIoqY5z3OG52rYgtcY9/tZ9Hc7+wqf8Af4Inq1bWg1y4cukperXP0f8ACbv7McIaJ1f/0OBx8at1Fdh+kGtI8hrP9pGrx6W1EOYJc0MAPZkguVGrJa2pjS8bWAGJ1nwVqzNqLmg2tgD3EHnXcmkS7/yCWbcSg7WtYDrwOwPu/tu2o9NNDbWkBoDB7NJ1j6Rn/CblTbm1B0te0TJBJ11U3Z2OAXbgdrdADqS7koES2sqspjhU2Mrre3k79oOvLnQ530vznKNnTsd73uDZa6HeYDdu5v8AJ3pm9QraQw2sJdo9/wAROn9VJnUaACd7Ru5E+UIetWiT7FjubtDPaWNYT39gD9zlXHSai5xkmYLW+Golun9pqM/PxWwG2NMxMH5QUhnYrid1rW66Gfl/mpXMBWjTHTzGh3bo9P4kDdu/k7kndKcbLNTAbLfjG73K03PpG2bWS2YM9oj/AKSk7Po2722s3QNJ5GmiJlPskmxTRu6ZYI2QZY08/nR7h/b/ADFUOPdt3bTBbvnyWv8AacVzvdcyBLgJ0B/dULL8V0D1GbY0aDxI/OSEj1CKcptFjg3SN5LWk+Ig/wAVH0bpj03TO2IPMTtWsLcYtc03M15k94/2Kv61XqT6o/nZny2R6idxIf/Z/+07qlBob3Rvc2hvcCAzLjAAOEJJTQQEAAAAAAChHAIAAAIAABwCUAARTmljaG9sYXMgTWNJbnRvc2gcAlUADFBob3RvZ3JhcGhlchwCbgAXqTIwMDkgTmljaG9sYXMgTWNJbnRvc2gcAgUAClN1cGVyIEJhYnkcAjcACDIwMDkwOTAzHAJ0ADZDb3B5cmlnaHQgqSAyMDA5IE5pY2hvbGFzIE1jSW50b3NoIEFMTCBSSUdIVFMgUkVTRVJWRUQAOEJJTQQlAAAAAAAQSd3zVsVSa1n78T1bM7gfQDhCSU0D6gAAAAAdsDw/eG1sIHZlcnNpb249IjEuMCIgZW5jb2Rpbmc9IlVURi04Ij8+CjwhRE9DVFlQRSBwbGlzdCBQVUJMSUMgIi0vL0FwcGxlIENvbXB1dGVyLy9EVEQgUExJU1QgMS4wLy9FTiIgImh0dHA6Ly93d3cuYXBwbGUuY29tL0RURHMvUHJvcGVydHlMaXN0LTEuMC5kdGQiPgo8cGxpc3QgdmVyc2lvbj0iMS4wIj4KPGRpY3Q+Cgk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNSG9yaXpvbnRhbFJlczwva2V5PgoJPGRpY3Q+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNyZWF0b3I8L2tleT4KCQk8c3RyaW5nPmNvbS5hcHBsZS5wcmludGluZ21hbmFnZXI8L3N0cmluZz4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuaXRlbUFycmF5PC9rZXk+CgkJPGFycmF5PgoJCQk8ZGljdD4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LlBhZ2VGb3JtYXQuUE1Ib3Jpem9udGFsUmVzPC9rZXk+CgkJCQk8cmVhbD43MjwvcmVhbD4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jbGllbnQ8L2tleT4KCQkJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lm1vZERhdGU8L2tleT4KCQkJCTxkYXRlPjIwMDktMDgtMjRUMTY6NDA6MzRaPC9kYXRlPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LnN0YXRlRmxhZzwva2V5PgoJCQkJPGludGVnZXI+MDwvaW50ZWdlcj4KCQkJPC9kaWN0PgoJCTwvYXJyYXk+Cgk8L2RpY3Q+Cgk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNT3JpZW50YXRpb248L2tleT4KCTxkaWN0PgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jcmVhdG9yPC9rZXk+CgkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lml0ZW1BcnJheTwva2V5PgoJCTxhcnJheT4KCQkJPGRpY3Q+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNT3JpZW50YXRpb248L2tleT4KCQkJCTxpbnRlZ2VyPjE8L2ludGVnZXI+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY2xpZW50PC9rZXk+CgkJCQk8c3RyaW5nPmNvbS5hcHBsZS5wcmludGluZ21hbmFnZXI8L3N0cmluZz4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5tb2REYXRlPC9rZXk+CgkJCQk8ZGF0ZT4yMDA5LTA4LTI0VDE2OjQwOjM0WjwvZGF0ZT4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5zdGF0ZUZsYWc8L2tleT4KCQkJCTxpbnRlZ2VyPjA8L2ludGVnZXI+CgkJCTwvZGljdD4KCQk8L2FycmF5PgoJPC9kaWN0PgoJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTVNjYWxpbmc8L2tleT4KCTxkaWN0PgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jcmVhdG9yPC9rZXk+CgkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lml0ZW1BcnJheTwva2V5PgoJCTxhcnJheT4KCQkJPGRpY3Q+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNU2NhbGluZzwva2V5PgoJCQkJPHJlYWw+MTwvcmVhbD4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jbGllbnQ8L2tleT4KCQkJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lm1vZERhdGU8L2tleT4KCQkJCTxkYXRlPjIwMDktMDgtMjRUMTY6NDA6MzRaPC9kYXRlPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LnN0YXRlRmxhZzwva2V5PgoJCQkJPGludGVnZXI+MDwvaW50ZWdlcj4KCQkJPC9kaWN0PgoJCTwvYXJyYXk+Cgk8L2RpY3Q+Cgk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNVmVydGljYWxSZXM8L2tleT4KCTxkaWN0PgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jcmVhdG9yPC9rZXk+CgkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lml0ZW1BcnJheTwva2V5PgoJCTxhcnJheT4KCQkJPGRpY3Q+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNVmVydGljYWxSZXM8L2tleT4KCQkJCTxyZWFsPjcyPC9yZWFsPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNsaWVudDwva2V5PgoJCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQubW9kRGF0ZTwva2V5PgoJCQkJPGRhdGU+MjAwOS0wOC0yNFQxNjo0MDozNFo8L2RhdGU+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuc3RhdGVGbGFnPC9rZXk+CgkJCQk8aW50ZWdlcj4wPC9pbnRlZ2VyPgoJCQk8L2RpY3Q+CgkJPC9hcnJheT4KCTwvZGljdD4KCTxrZXk+Y29tLmFwcGxlLnByaW50LlBhZ2VGb3JtYXQuUE1WZXJ0aWNhbFNjYWxpbmc8L2tleT4KCTxkaWN0PgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jcmVhdG9yPC9rZXk+CgkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lml0ZW1BcnJheTwva2V5PgoJCTxhcnJheT4KCQkJPGRpY3Q+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNVmVydGljYWxTY2FsaW5nPC9rZXk+CgkJCQk8cmVhbD4xPC9yZWFsPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNsaWVudDwva2V5PgoJCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQubW9kRGF0ZTwva2V5PgoJCQkJPGRhdGU+MjAwOS0wOC0yNFQxNjo0MDozNFo8L2RhdGU+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuc3RhdGVGbGFnPC9rZXk+CgkJCQk8aW50ZWdlcj4wPC9pbnRlZ2VyPgoJCQk8L2RpY3Q+CgkJPC9hcnJheT4KCTwvZGljdD4KCTxrZXk+Y29tLmFwcGxlLnByaW50LnN1YlRpY2tldC5wYXBlcl9pbmZvX3RpY2tldDwva2V5PgoJPGRpY3Q+CgkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTUFkanVzdGVkUGFnZVJlY3Q8L2tleT4KCQk8ZGljdD4KCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNyZWF0b3I8L2tleT4KCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQkJPGFycmF5PgoJCQkJPGRpY3Q+CgkJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTUFkanVzdGVkUGFnZVJlY3Q8L2tleT4KCQkJCQk8YXJyYXk+CgkJCQkJCTxyZWFsPjAuMDwvcmVhbD4KCQkJCQkJPHJlYWw+MC4wPC9yZWFsPgoJCQkJCQk8cmVhbD43MzQ8L3JlYWw+CgkJCQkJCTxyZWFsPjU3NjwvcmVhbD4KCQkJCQk8L2FycmF5PgoJCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jbGllbnQ8L2tleT4KCQkJCQk8c3RyaW5nPmNvbS5hcHBsZS5wcmludGluZ21hbmFnZXI8L3N0cmluZz4KCQkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQubW9kRGF0ZTwva2V5PgoJCQkJCTxkYXRlPjIwMDktMDktMDNUMTg6MDQ6NTRaPC9kYXRlPgoJCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5zdGF0ZUZsYWc8L2tleT4KCQkJCQk8aW50ZWdlcj4wPC9pbnRlZ2VyPgoJCQkJPC9kaWN0PgoJCQk8L2FycmF5PgoJCTwvZGljdD4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNQWRqdXN0ZWRQYXBlclJlY3Q8L2tleT4KCQk8ZGljdD4KCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNyZWF0b3I8L2tleT4KCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQkJPGFycmF5PgoJCQkJPGRpY3Q+CgkJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTUFkanVzdGVkUGFwZXJSZWN0PC9rZXk+CgkJCQkJPGFycmF5PgoJCQkJCQk8cmVhbD4tMTg8L3JlYWw+CgkJCQkJCTxyZWFsPi0xODwvcmVhbD4KCQkJCQkJPHJlYWw+Nzc0PC9yZWFsPgoJCQkJCQk8cmVhbD41OTQ8L3JlYWw+CgkJCQkJPC9hcnJheT4KCQkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY2xpZW50PC9rZXk+CgkJCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lm1vZERhdGU8L2tleT4KCQkJCQk8ZGF0ZT4yMDA5LTA5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op="http://ns.adobe.com/photoshop/1.0/" xmlns:xapMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmlns:xapRights="http://ns.adobe.com/xap/1.0/rights/" xmlns:Iptc4xmpCore="http://iptc.org/std/Iptc4xmpCore/1.0/xmlns/" tiff:Make="NIKON CORPORATION" tiff:Model="NIKON D300" tiff:XResolution="3000000/10000" tiff:YResolution="3000000/10000" tiff:ResolutionUnit="2" tiff:Orientation="1" tiff:NativeDigest="256,257,258,259,262,274,277,284,530,531,282,283,296,301,318,319,529,532,306,270,271,272,305,315,33432;E745CBE401E64591D4439C9C916785EE" tiff:ImageWidth="2848" tiff:ImageLength="4288" tiff:Compression="5" tiff:PhotometricInterpretation="2" tiff:SamplesPerPixel="3" tiff:PlanarConfiguration="1" exif:ExifVersion="0221" exif:ExposureTime="1/200" exif:ShutterSpeedValue="7643856/1000000" exif:ExposureProgram="1" exif:DateTimeOriginal="2009-02-06T14:41:30.66-05:00" exif:DateTimeDigitized="2009-02-06T14:41:30.66-05:00" exif:ExposureBiasValue="0/6" exif:MaxApertureValue="0/10" exif:MeteringMode="2" exif:LightSource="9" exif:SensingMethod="2" exif:FileSource="3" exif:SceneType="1" exif:CustomRendered="0" exif:ExposureMode="1" exif:WhiteBalance="1" exif:SceneCaptureType="0" exif:GainControl="0" exif:Contrast="0" exif:Saturation="0" exif:Sharpness="0" exif:SubjectDistanceRange="0" exif:DigitalZoomRatio="1/1" exif:PixelXDimension="341" exif:PixelYDimension="508" exif:ColorSpace="1" exif:NativeDigest="36864,40960,40961,37121,37122,40962,40963,37510,40964,36867,36868,33434,33437,34850,34852,34855,34856,37377,37378,37379,37380,37381,37382,37383,37384,37385,37386,37396,41483,41484,41486,41487,41488,41492,41493,41495,41728,41729,41730,41985,41986,41987,41988,41989,41990,41991,41992,41993,41994,41995,41996,42016,0,2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,20,22,23,24,25,26,27,28,30;1CB598CA387F8C47EF5461B79A30B56C" xap:ModifyDate="2009-09-03T15:21:50-04:00" xap:CreateDate="2009-09-03T15:21:50-04:00" xap:CreatorTool="Adobe Photoshop CS3 Macintosh" xap:Rating="5" xap:MetadataDate="2009-09-03T15:21:50-04:00" aux:SerialNumber="3014784" aux:LensInfo="0/10 0/10 0/10 0/10" aux:Lens="0.0 mm f/0.0" aux:ImageNumber="45768" crs:RawFileName="NMP.090206.0125.NEF" crs:Version="4.6" crs:WhiteBalance="As Shot" crs:Temperature="5000" crs:Tint="+1" crs:Exposure="-0.75" crs:Shadows="8" crs:Brightness="+50" crs:Contrast="+15" crs:Saturation="+26" crs:Sharpness="51" crs:LuminanceSmoothing="0" crs:ColorNoiseReduction="25" crs:ChromaticAberrationR="0" crs:ChromaticAberrationB="0" crs:VignetteAmount="0" crs:ShadowTint="0" crs:RedHue="0" crs:RedSaturation="0" crs:GreenHue="0" crs:GreenSaturation="0" crs:BlueHue="0" crs:BlueSaturation="0" crs:FillLight="14" crs:Vibrance="+13" crs:HighlightRecovery="0" crs:Clarity="+60" crs:Defringe="1" crs:HueAdjustmentRed="0" crs:HueAdjustmentOrange="0" crs:HueAdjustmentYellow="0" crs:HueAdjustmentGreen="0" crs:HueAdjustmentAqua="0" crs:HueAdjustmentBlue="0" crs:HueAdjustmentPurple="0" crs:HueAdjustmentMagenta="0" crs:SaturationAdjustmentRed="0" crs:SaturationAdjustmentOrange="0" crs:SaturationAdjustmentYellow="-43" crs:SaturationAdjustmentGreen="0" crs:SaturationAdjustmentAqua="0" crs:SaturationAdjustmentBlue="0" crs:SaturationAdjustmentPurple="0" crs:SaturationAdjustmentMagenta="0" crs:LuminanceAdjustmentRed="0" crs:LuminanceAdjustmentOrange="0" crs:LuminanceAdjustmentYellow="0" crs:LuminanceAdjustmentGreen="0" crs:LuminanceAdjustmentAqua="0" crs:LuminanceAdjustmentBlue="0" crs:LuminanceAdjustmentPurple="0" crs:LuminanceAdjustmentMagenta="0" crs:SplitToningShadowHue="0" crs:SplitToningShadowSaturation="0" crs:SplitToningHighlightHue="0" crs:SplitToningHighlightSaturation="0" crs:SplitToningBalance="0" crs:ParametricShadows="0" crs:ParametricDarks="0" crs:ParametricLights="0" crs:ParametricHighlights="0" crs:ParametricShadowSplit="25" crs:ParametricMidtoneSplit="50" crs:ParametricHighlightSplit="75" crs:SharpenRadius="+1.0" crs:SharpenDetail="73" crs:SharpenEdgeMasking="95" crs:PostCropVignetteAmount="0" crs:ConvertToGrayscale="False" crs:ToneCurveName="Medium Contrast" crs:CameraProfile="ACR 4.4" crs:CameraProfileDigest="F3ECC1496F73CCB1E2CCA8DCD725018D" crs:HasSettings="True" crs:HasCrop="False" crs:AlreadyApplied="True" dc:format="image/jpeg" photoshop:ColorMode="3" photoshop:ICCProfile="sRGB IEC61966-2.1" photoshop:AuthorsPosition="Photographer" photoshop:DateCreated="2009-09-03" photoshop:Credit="©2009 Nicholas McIntosh" photoshop:History="" xapMM:InstanceID="uuid:D53B3EF29A2F11DEBE908B51C32AE956" xapMM:DocumentID="uuid:CA25CB4C9A2D11DEBE908B51C32AE956" xapRights:Marked="True" xapRights:WebStatement="http://www.NicholasMcIntosh.com"> <tiff:BitsPerSample> <rdf:Seq> <rdf:li>8</rdf:li> <rdf:li>8</rdf:li> <rdf:li>8</rdf:li> </rdf:Seq> </tiff:BitsPerSample> <exif:ISOSpeedRatings> <rdf:Seq> <rdf:li>200</rdf:li> </rdf:Seq> </exif:ISOSpeedRatings> <exif:Flash exif:Fired="False" exif:Return="0" exif:Mode="0" exif:Function="False" exif:RedEyeMode="False"/> <exif:UserComment> <rdf:Alt> <rdf:li xml:lang="x-default">(C)NICHOLAS_McINTOSH_PHOTOGRAPHY</rdf:li> </rdf:Alt> </exif:UserComment> <crs:ToneCurve> <rdf:Seq> <rdf:li>0, 0</rdf:li> <rdf:li>32, 22</rdf:li> <rdf:li>64, 56</rdf:li> <rdf:li>128, 128</rdf:li> <rdf:li>192, 196</rdf:li> <rdf:li>255, 255</rdf:li> </rdf:Seq> </crs:ToneCurve> <dc:title> <rdf:Alt> <rdf:li xml:lang="x-default">Super Baby</rdf:li> </rdf:Alt> </dc:title> <dc:creator> <rdf:Seq> <rdf:li>Nicholas McIntosh</rdf:li> </rdf:Seq> </dc:creator> <dc:rights> <rdf:Alt> <rdf:li xml:lang="x-default">Copyright © 2009 Nicholas McIntosh ALL RIGHTS RESERVED</rdf:li> </rdf:Alt> </dc:rights> <xapMM:DerivedFrom stRef:instanceID="uuid:CA25CB479A2D11DEBE908B51C32AE956" stRef:documentID="uuid:3BFA8AF291B211DEAFFBAC265E129096"/> <xapRights:UsageTerms> <rdf:Alt> <rdf:li xml:lang="x-default">All rights reserved © 2009 Nicholas McIntosh&#xA;No usage authorized without prior written permission</rdf:li> </rdf:Alt> </xapRights:UsageTerms> <Iptc4xmpCore:CreatorContactInfo Iptc4xmpCore:CiAdrExtadr="4115 Church Rd" Iptc4xmpCore:CiAdrCity="Manchester" Iptc4xmpCore:CiAdrRegion="Maryland" Iptc4xmpCore:CiAdrPcode="21102" Iptc4xmpCore:CiTelWork="+1 (443) 804-8516" Iptc4xmpCore:CiAdrCtry="USA" Iptc4xmpCore:CiEmailWork="nm@nicholasmcintosh.com" Iptc4xmpCore:CiUrlWork="http://NicholasMcIntosh.com"/> </rdf:Description> </rdf:RDF> </x:xmpmeta>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            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";
    var canvas = document.getElementById('canvas');
    var context = canvas.getContext('2d');
    context.drawImage(im, 0, 0);
    var imageData = context.getImageData(0, 0, 100, 100);
    var buf32 = new Uint32Array(imageData.buffer);
    var red, green, blue;
   
    function clamp(lo, value, hi) {
      return value < lo ? lo : value > hi ? hi : value;
    }
   
    function nearest(pixels, x, y, offset, width) {
      return (pixels[((y + 0.5) | 0) * width + ((x + 0.5) | 0)] >> (offset << 8)) & 0xff;
    }
   
    function nearest_unrolled(pixels, x, y, width) {
      return pixels[((y + 0.5) | 0) * width + ((x + 0.5) | 0)];
    }
   
    function bilinear(pixels, x, y, offset, width) {
      var xf = x | 0;
      var yf = y | 0;
      var xt = xf + 1;
      var yt = yf + 1;
   
      var percentX = 1.0 - (x - xf);
      var percentY = y - yf;
   
      offset <<= 8;
   
      var top = ((pixels[offset + yt * width + xf] >> offset) & 0xff) * percentX + ((pixels[offset + yt * width + xt] >> offset) & 0xff) * (1.0 - percentX);
      var bottom = ((pixels[offset + yf * width + xf] >> offset) & 0xff) * percentX + ((pixels[offset + yf * width + xt] >> offset) & 0xff) * (1.0 - percentX);
   
      return top * percentY + bottom * (1.0 - percentY);
    }
   
    function bilinear_optimized(pixels, x, y, offset, width) {
      var percentX = x - (x | 0);
      var percentX1 = 1.0 - percentX;
      var percentY = y - (y | 0);
      var fx4 = (x | 0);
      var cx4 = fx4 + 1;
      var fy4 = (y | 0);
      var cy4wo = (fy4 + 1) * width;
      var fy4wo = fy4 * width;
      offset <<= 8;
      var top = ((pixels[cy4wo + fx4] >> offset) & 0xff) * percentX1 + ((pixels[cy4wo + cx4] >> offset) & 0xff) * percentX;
      var bottom = ((pixels[fy4wo + fx4] >> offset) & 0xff) * percentX1 + ((pixels[fy4wo + cx4] >> offset) & 0xff) * percentX;
   
      return top * percentY + bottom * (1.0 - percentY);
    }
   
    function bilinear_unrolled(pixels, x, y, width) {
      var xf = (x | 0);
      var yf = (y | 0);
   
      var percentX = x - xf;
      var percentX1 = 1.0 - percentX;
      var percentY = y - yf;
      var percentY1 = 1.0 - percentY;
   
      var idx = xf + yf * width;
      var top, bottom, r, g, b;
   
      var p00 = pixels[idx];
      var p10 = pixels[idx + 1];
      var p11 = pixels[idx + width + 1];
      var p01 = pixels[idx + width];
   
      top = ((p00 >> 16) & 0xff) * percentX1 + ((p10 >> 16) & 0xff) * percentX;
      bottom = ((p01 >> 16) & 0xff) * percentX1 + ((p11 >> 16) & 0xff) * percentX;
      r = top * percentY + bottom * percentY1;
   
      top = ((p00 >> 8) & 0xff) * percentX1 + ((p10 >> 8) & 0xff) * percentX;
      bottom = ((p01 >> 8) & 0xff) * percentX1 + ((p11 >> 8) & 0xff) * percentX;
      g = top * percentY + bottom * percentY1;
   
      top = (p00 & 0xff) * percentX1 + (p10 & 0xff) * percentX;
      bottom = (p01 & 0xff) * percentX1 + (p11 & 0xff) * percentX;
      b = top * percentY + bottom * percentY1;
   
      return [r, g, b];
    }
   
    function bicubic_value(x, a, b, c, d) {
      return clamp(0, 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * x) * x) * x + b, 255);
    }
   
    function bicubic(pixels, x, y, offset, width) {
      var v = [0, 0, 0, 0];
      var fx = (x | 0);
      var fy = (y | 0);
      var percentX = x - fx;
      var percentY = y - fy;
      offset <<= 8;
   
      for (var i = -1; i < 3; i++) {
        var yw4o = (fy + i) * width * 4 + offset;
        v[i + 1] = (bicubic_value(percentX, ((pixels[(fy + i) * width + (fx - 1)] >> offset) & 0xff), ((pixels[(fy + i) * width + fx] >> offset) & 0xff), ((pixels[(fy + i) * width + (fx + 1)] >> offset) & 0xff), ((pixels[(fy + i) * width + (fx + 2)] >> offset) & 0xff)));
      }
   
      return (bicubic_value(percentY, v[0], v[1], v[2], v[3])) | 0;
    }
   
    function bicubic_optimized(pixels, x, y, offset, width) {
      var a, b, c, d, v0, v1, v2, v3;
      var fx = x | 0;
      var fy = y | 0;
      var percentX = x - fx;
      var percentY = y - fy;
   
      var fx14 = fx;
      var fx04 = fx14 - 1;
      var fx24 = fx14 + 2;
      var fx34 = fx14 + 3;
      var w4 = width;
   
      var yw14o = fy * w4;
      var yw04o = yw14o - w4;
      var yw24o = yw14o + w4;
      var yw34o = yw14o + w4 + w4;
   
      offset <<= 8;
   
      a = ((pixels[yw04o + fx04] >> offset) & 0xff);
      b = ((pixels[yw04o + fx14] >> offset) & 0xff);
      c = ((pixels[yw04o + fx24] >> offset) & 0xff);
      d = ((pixels[yw04o + fx34] >> offset) & 0xff);
      v0 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v0 = v0 > 255 ? 255 : v0 < 0 ? 0 : v0;
   
      a = ((pixels[yw14o + fx04] >> offset) & 0xff);
      b = ((pixels[yw14o + fx14] >> offset) & 0xff);
      c = ((pixels[yw14o + fx24] >> offset) & 0xff);
      d = ((pixels[yw14o + fx34] >> offset) & 0xff);
      v1 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v1 = v1 > 255 ? 255 : v1 < 0 ? 0 : v1;
   
      a = ((pixels[yw24o + fx04] >> offset) & 0xff);
      b = ((pixels[yw24o + fx14] >> offset) & 0xff);
      c = ((pixels[yw24o + fx24] >> offset) & 0xff);
      d = ((pixels[yw24o + fx34] >> offset) & 0xff);
      v2 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v2 = v2 > 255 ? 255 : v2 < 0 ? 0 : v2;
   
      a = ((pixels[yw34o + fx04] >> offset) & 0xff);
      b = ((pixels[yw34o + fx14] >> offset) & 0xff);
      c = ((pixels[yw34o + fx24] >> offset) & 0xff);
      d = ((pixels[yw34o + fx34] >> offset) & 0xff);
      v3 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v3 = v3 > 255 ? 255 : v3 < 0 ? 0 : v3;
   
      a = v0;
      b = v1;
      c = v2;
      d = v3;
      a = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentY) * percentY) * percentY + b;
      return a > 255 ? 255 : a < 0 ? 0 : a ^ 0;
    }
   
    function bicubic_unrolled(pixels, x, y, width) {
      var a, b, c, d, v0, v1, v2, v3, r, g, b;
      var fx = x | 0;
      var fy = y | 0;
      var percentX = x - fx;
      var percentY = y - fy;
   
      var fx14 = fx;
      var fx04 = fx14 - 1;
      var fx24 = fx14 + 1;
      var fx34 = fx14 + 2;
      var w4 = width;
      var yw14r = fy * w4;
      var yw04r = yw14r - w4;
      var yw24r = yw14r + w4;
      var yw34r = yw14r + w4 + w4;
   
      var ca1 = pixels[yw04r + fx04];
      var cb1 = pixels[yw04r + fx04];
      var cc1 = pixels[yw04r + fx04];
      var cd1 = pixels[yw04r + fx04];
   
      var ca2 = pixels[yw14r + fx04];
      var cb2 = pixels[yw14r + fx14];
      var cc2 = pixels[yw14r + fx24];
      var cd2 = pixels[yw14r + fx34];
   
      var ca3 = pixels[yw24r + fx04];
      var cb3 = pixels[yw24r + fx14];
      var cc3 = pixels[yw24r + fx24];
      var cd3 = pixels[yw24r + fx34];
   
      var ca4 = pixels[yw34r + fx04];
      var cb4 = pixels[yw34r + fx14];
      var cc4 = pixels[yw34r + fx24];
      var cd4 = pixels[yw34r + fx34];
   
      // Red
      a = (ca1 & 0xff0000) >> 16;
      b = (cb1 & 0xff0000) >> 16;
      c = (cc1 & 0xff0000) >> 16;
      d = (cd1 & 0xff0000) >> 16;
      v0 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v0 = v0 > 255 ? 255 : v0 < 0 ? 0 : v0;
   
      a = (ca2 & 0xff0000) >> 16;
      b = (cb2 & 0xff0000) >> 16;
      c = (cc2 & 0xff0000) >> 16;
      d = (cd2 & 0xff0000) >> 16;
      v1 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v1 = v1 > 255 ? 255 : v1 < 0 ? 0 : v1;
   
      a = (ca3 & 0xff0000) >> 16;
      b = (cb3 & 0xff0000) >> 16;
      c = (cc3 & 0xff0000) >> 16;
      d = (cd3 & 0xff0000) >> 16;
      v2 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v2 = v2 > 255 ? 255 : v2 < 0 ? 0 : v2;
   
      a = (ca4 & 0xff0000) >> 16;
      b = (cb4 & 0xff0000) >> 16;
      c = (cc4 & 0xff0000) >> 16;
      d = (cd4 & 0xff0000) >> 16;
      v3 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v3 = v3 > 255 ? 255 : v3 < 0 ? 0 : v3;
   
      a = v0;
      b = v1;
      c = v2;
      d = v3;
      r = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentY) * percentY) * percentY + b;
      r = r > 255 ? 255 : r < 0 ? 0 : r ^ 0;
   
      // Green
      a = (ca1 & 0xff00) >> 8;
      b = (cb1 & 0xff00) >> 8;
      c = (cc1 & 0xff00) >> 8;
      d = (cd1 & 0xff00) >> 8;
      v0 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v0 = v0 > 255 ? 255 : v0 < 0 ? 0 : v0;
   
      a = (ca2 & 0xff00) >> 8;
      b = (cb2 & 0xff00) >> 8;
      c = (cc2 & 0xff00) >> 8;
      d = (cd2 & 0xff00) >> 8;
      v1 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v1 = v1 > 255 ? 255 : v1 < 0 ? 0 : v1;
   
      a = (ca3 & 0xff00) >> 8;
      b = (cb3 & 0xff00) >> 8;
      c = (cc3 & 0xff00) >> 8;
      d = (cd3 & 0xff00) >> 8;
      v2 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v2 = v2 > 255 ? 255 : v2 < 0 ? 0 : v2;
   
      a = (ca4 & 0xff00) >> 8;
      b = (cb4 & 0xff00) >> 8;
      c = (cc4 & 0xff00) >> 8;
      d = (cd4 & 0xff00) >> 8;
      v3 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v3 = v3 > 255 ? 255 : v3 < 0 ? 0 : v3;
   
      a = v0;
      b = v1;
      c = v2;
      d = v3;
      g = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentY) * percentY) * percentY + b;
      g = g > 255 ? 255 : g < 0 ? 0 : g ^ 0;
   
      // Blue
      a = ca1 & 0xff;
      b = cb1 & 0xff;
      c = cc1 & 0xff;
      d = cd1 & 0xff;
      v0 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v0 = v0 > 255 ? 255 : v0 < 0 ? 0 : v0;
   
      a = ca2 & 0xff;
      b = cb2 & 0xff;
      c = cc2 & 0xff;
      d = cd2 & 0xff;
      v1 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v1 = v1 > 255 ? 255 : v1 < 0 ? 0 : v1;
   
      a = ca3 & 0xff;
      b = cb3 & 0xff;
      c = cc3 & 0xff;
      d = cd3 & 0xff;
      v2 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v2 = v2 > 255 ? 255 : v2 < 0 ? 0 : v2;
   
      a = ca4 & 0xff;
      b = cb4 & 0xff;
      c = cc4 & 0xff;
      d = cd4 & 0xff;
      v3 = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentX) * percentX) * percentX + b;
      v3 = v3 > 255 ? 255 : v3 < 0 ? 0 : v3;
   
      a = v0;
      b = v1;
      c = v2;
      d = v3;
      b = 0.5 * (c - a + (2.0 * a - 5.0 * b + 4.0 * c - d + (3.0 * (b - c) + d - a) * percentY) * percentY) * percentY + b;
      b = b > 255 ? 255 : b < 0 ? 0 : b ^ 0;
   
      return [r, g, b];
    }
   
    //returns a function that calculates lanczos weight
   
    function lanczosCreate(lobes) {
      return function(x) {
        if (x > lobes)
          return 0;
        x *= Math.PI;
        if (Math.abs(x) < 1e-16)
          return 1
        var xx = x / lobes;
        return Math.sin(x) * Math.sin(xx) / x / xx;
      }
    }
   
    //elem: canvas element, img: image element, sx: scaled width, lobes: kernel radius
   
    function thumbnailer(elem, img, sx, lobes) {
      this.canvas = elem;
      elem.width = img.width;
      elem.height = img.height;
      elem.style.display = "none";
      this.ctx = elem.getContext("2d");
      this.ctx.drawImage(img, 0, 0);
      this.img = img;
      this.src = this.ctx.getImageData(0, 0, img.width, img.height);
      this.dest = {
        width: sx,
        height: Math.round(img.height * sx / img.width),
      };
      this.dest.data = new Array(this.dest.width * this.dest.height * 3);
      this.lanczos = lanczosCreate(lobes);
      this.ratio = img.width / sx;
      this.rcp_ratio = 2 / this.ratio;
      this.range2 = Math.ceil(this.ratio * lobes / 2);
      this.cacheLanc = {};
      this.center = {};
      this.icenter = {};
      setTimeout(this.process1, 0, this, 0);
    }
   
    thumbnailer.prototype.process1 = function(self, u) {
      self.center.x = (u + 0.5) * self.ratio;
      self.icenter.x = Math.floor(self.center.x);
      for (var v = 0; v < self.dest.height; v++) {
        self.center.y = (v + 0.5) * self.ratio;
        self.icenter.y = Math.floor(self.center.y);
        var a, r, g, b;
        a = r = g = b = 0;
        for (var i = self.icenter.x - self.range2; i <= self.icenter.x + self.range2; i++) {
          if (i < 0 || i >= self.src.width)
            continue;
          var f_x = Math.floor(1000 * Math.abs(i - self.center.x));
          if (!self.cacheLanc[f_x])
            self.cacheLanc[f_x] = {};
          for (var j = self.icenter.y - self.range2; j <= self.icenter.y + self.range2; j++) {
            if (j < 0 || j >= self.src.height)
              continue;
            var f_y = Math.floor(1000 * Math.abs(j - self.center.y));
            if (self.cacheLanc[f_x][f_y] == undefined)
              self.cacheLanc[f_x][f_y] = self.lanczos(Math.sqrt(Math.pow(f_x * self.rcp_ratio, 2) + Math.pow(f_y * self.rcp_ratio, 2)) / 1000);
            weight = self.cacheLanc[f_x][f_y];
            if (weight > 0) {
              var idx = (j * self.src.width + i) * 4;
              a += weight;
              r += weight * self.src.data[idx];
              g += weight * self.src.data[idx + 1];
              b += weight * self.src.data[idx + 2];
            }
          }
        }
        var idx = (v * self.dest.width + u) * 3;
        self.dest.data[idx] = r / a;
        self.dest.data[idx + 1] = g / a;
        self.dest.data[idx + 2] = b / a;
      }
   
      if (++u < self.dest.width)
        setTimeout(self.process1, 0, self, u);
      else
        setTimeout(self.process2, 0, self);
    };
    thumbnailer.prototype.process2 = function(self) {
      self.canvas.width = self.dest.width;
      self.canvas.height = self.dest.height;
      self.ctx.drawImage(self.img, 0, 0);
      self.src = self.ctx.getImageData(0, 0, self.dest.width, self.dest.height);
      var idx, idx2;
      for (var i = 0; i < self.dest.width; i++) {
        for (var j = 0; j < self.dest.height; j++) {
          idx = (j * self.dest.width + i) * 3;
          idx2 = (j * self.dest.width + i) * 4;
          self.src.data[idx2] = self.dest.data[idx];
          self.src.data[idx2 + 1] = self.dest.data[idx + 1];
          self.src.data[idx2 + 2] = self.dest.data[idx + 2];
        }
      }
      self.ctx.putImageData(self.src, 0, 0);
      self.canvas.style.display = "block";
    }
};
</script>

Preparation code output

Test runner

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Testing in unknown unknown
Test Ops/sec
Nearest Neighbor
var red = nearest(buf32, 10.2, 4.6, 0, canvas.width);
var green = nearest(buf32, 10.2, 4.6, 1, canvas.width);
var blue = nearest(buf32, 10.2, 4.6, 2, canvas.width);
pending…
Nearest Neighbor Optimized Unrolled
var rgb = nearest_unrolled(buf32, 10.2, 4.6, canvas.width);
pending…
Bilinear
var red = bilinear(buf32, 10.2, 4.6, 0, canvas.width);
var green = bilinear(buf32, 10.2, 4.6, 1, canvas.width);
var blue = bilinear(buf32, 10.2, 4.6, 2, canvas.width);
pending…
Bilinear Optimized
var red = bilinear_optimized(buf32, 10.2, 4.6, 0, canvas.width);
var green = bilinear_optimized(buf32, 10.2, 4.6, 1, canvas.width);
var blue = bilinear_optimized(buf32, 10.2, 4.6, 2, canvas.width);
pending…
Bilinear Optimized Unrolled
var rgb = bilinear_unrolled(buf32, 10.2, 4.6, canvas.width);
pending…
Bicubic
var red = bicubic(buf32, 10.2, 4.6, 0, canvas.width);
var green = bicubic(buf32, 10.2, 4.6, 1, canvas.width);
var blue = bicubic(buf32, 10.2, 4.6, 2, canvas.width);
pending…
Bicubic Optimized
var red = bicubic_optimized(buf32, 10.2, 4.6, 0, canvas.width);
var green = bicubic_optimized(buf32, 10.2, 4.6, 1, canvas.width);
var blue = bicubic_optimized(buf32, 10.2, 4.6, 2, canvas.width);
pending…
Bicubic Optimized Unrolled
var rgb = bicubic_unrolled(buf32, 10.2, 4.6, canvas.width);
pending…

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