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Reconstruction filter

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filter, then using the discrete resampling filter to directly resample the image. For decimation by an integer amount, only a single sampled filter is necessary; for interpolation by an integer amount, different samplings are needed for different phases – for instance, if one is upsampling by a factor of 4, then one sampled filter is used for the half-way point, while a different sampled filter is used for the point 1/4 of the way from one point to another.
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In photography, a great variety of interpolation filters exist, some proprietary, for which opinions are mixed. Evaluation is often subjective, with reactions being varied, and some arguing that at realistic resampling ratios, there is little difference between them, as compared with bicubic, though
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of higher order – the box filter and tent filter being the 0th and 1st order cardinal B-splines. These filters fail to be interpolating filters, since their impulse response do not vanish at all non-zero original sample points – for 1:1 resampling, they are not the identity, but rather blur. On the
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waveform has an infinite response to a signal, in both the positive and negative time directions, which is impossible to perform in real time – as it would require infinite delay. Consequently, real reconstruction filters typically either allow some energy above the Nyquist rate, attenuate some
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For reconstruction purposes, a variety of kernels are used, many of which can be interpreted as approximating the sinc function, either by windowing or by giving a spline approximation, either by cubics or higher order splines. In the case of windowed sinc filters, the frequency response of the
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For resampling, in principle the analog image is reconstructed, then sampled, and this is necessary for general changes in resolution. For integer ratios of sampling rate, one may simplify by sampling the impulse response of the continuous reconstruction filter to produce a discrete resampling
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reconstruction filter can be understood in terms of the frequency response of the window, as the frequency response of a windowed filter is the convolution of the original response (for sinc, a brick-wall) with the frequency response of the window. Among these, the
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A subtlety in image processing is that (linear) signal processing assumes linear luminance – that doubling a pixel value doubles the luminance of the output. However, images are frequently
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color space, so luminance is not linear. Thus to apply a linear filter, one must first gamma decode the values – and if resampling, one must gamma decode, resample, then gamma encode.
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and a reconstruction filter may be of identical design. For example, both the input and the output for audio equipment may be sampled at 44.1 kHz. In this case, both
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Alternatively, a system may have no reconstruction filter and simply tolerate some energy being wasted reproducing higher frequency images of the primary signal spectrum.
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signal must be bandlimited, to prevent imaging (meaning Fourier coefficients being reconstructed as spurious high-frequency 'mirrors'). This is an implementation of the
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of the signal is also known, in addition to the amplitude, and conversely that also performing derivative reconstruction can improve signal reconstruction methods.
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Medical Image Computing and Computer-Assisted Intervention--MICCAI '99: second international conference, Cambridge, UK, September 19–22, 1999 proceedings
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Practical filters have non-flat frequency or phase response in the pass band and incomplete suppression of the signal elsewhere. The ideal
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may be used to ensure that frequencies of interest are accurately reproduced without excess energy being emitted out of band.
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For the same reason, the output of a DAC requires a low-pass analog filter, called a reconstruction filter - because the
550: 24: 458: 385: 35:, is used to construct a smooth analog signal from a digital input, as in the case of a digital to analog converter ( 240:– this latter has a free parameter, with each value of the parameter yielding a different interpolation filter. 221: 187: 360: 273: 412: 97:, constant phase delay in the pass-band with constant flat frequency response, and zero response from the 52: 36: 117:, in practice, a real DAC outputs pulses with finite bandwidth and width. Both idealized Dirac pulses, 292:
Reconstruction filters are also used when "reconstructing" a waveform or an image from a collection of
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steps and other output pulses, if unfiltered, would contain spurious high-frequency replicas, "
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These are in increasing order of stopband suppression (anti-aliasing), and decreasing speed
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block as much as possible above 22 kHz and pass as much as possible below 20 kHz.
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Quantitative Comparison of Sinc-Approximating Kernels for Medical Image Interpolation
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ACM SIGGRAPH International Conference on Computer Graphics and Interactive Techniques
381: 329: 269: 260: 171:, digital reconstruction filters are used both to recreate images from samples as in 130: 98: 56: 497: 446: 373: 202: 168: 94: 48: 484: 297: 224:, with kernel the box filter – for downsampling, this corresponding to averaging; 172: 126: 118: 249: 544: 253: 191: 137: 102: 20: 532: 358: 237: 153: 142: 377: 450: 68: 359:
Theußl, Thomas; Hauser, Helwig; Gröller, Meister Eduard (October 2000).
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other hand, being nonnegative, they do not introduce any overshoot or
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Filter used to construct a smooth analog signal from a digital input
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for higher resampling ratios behavior is more varied.
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Mitchell, Don P.; Netravali, Arun N. (August 1988).
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Another class of reconstruction filters include the
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IEEE/ACM SIGGRAPH Symposium on Volume Visualization
113:While in theory a DAC outputs a series of discrete 477:Meijering, Erik H. W.; Niessen; Pluim; Viergever. 287: 542: 141:in-band frequencies, or both. For this reason, 300:, a common technique is to use a number of 2D 75:(here meaning waves of higher frequency being 435:Reconstruction filters in computer-graphics 362:Mastering Windows: Improving Reconstruction 101:. This can be achieved by a filter with a ' 427: 425: 410: 217:The most common day-to-day filters are: 422: 88:Whittaker–Shannon interpolation formula 39:) or other sampled data output device. 543: 472: 470: 406: 404: 402: 413:"Filters for Common Resampling Tasks" 354: 352: 350: 467: 399: 162: 43:Sampled data reconstruction filters 13: 510:Digital Photo Interpolation Review 445:. Vol. 22. pp. 221–228. 14: 572: 347: 212: 186:Resampling may be referred to as 108: 263:for various widths, or cardinal 93:Ideally, both filters should be 148:In systems that have both, the 561:Electronic filter applications 526: 514: 503: 491: 288:Wavelet reconstruction filters 230:, with kernel the tent filter; 222:nearest-neighbor interpolation 51:describes why the input of an 1: 340: 308:to "reconstruct" a 3D image. 274:Fourier uncertainty principle 7: 323: 55:requires a low-pass analog 10: 577: 19:In a mixed-signal system ( 551:Digital signal processing 318:Iterative reconstruction 313:Reconstruction algorithm 256:are frequently praised. 521:Interpolation -- Part I 498:dpreview: Interpolation 411:Turkowski, Ken (1990). 79:as a lower frequency). 228:bilinear interpolation 31:, sometimes called an 500:, by Vincent Bockaert 378:10.1109/VV.2000.10002 335:Signal reconstruction 234:bicubic interpolation 29:reconstruction filter 533:Image Filter - Sepia 451:10.1145/54852.378514 150:anti-aliasing filter 105:' impulse response. 61:anti-aliasing filter 129:(copies) above the 33:anti-imaging filter 330:Signal processing 296:coefficients. In 270:ringing artifacts 205:, notably in the 127:image frequencies 99:Nyquist frequency 95:brickwall filters 57:electronic filter 568: 535: 530: 524: 518: 512: 507: 501: 495: 489: 488: 474: 465: 464: 440: 429: 420: 419: 417: 408: 397: 391: 367: 356: 280:("scalloping"). 236:, with kernel a 169:image processing 163:Image processing 49:sampling theorem 576: 575: 571: 570: 569: 567: 566: 565: 541: 540: 539: 538: 531: 527: 519: 515: 508: 504: 496: 492: 475: 468: 461: 438: 430: 423: 415: 409: 400: 394:Project webpage 388: 365: 357: 348: 343: 326: 298:medical imaging 290: 215: 173:medical imaging 165: 119:zero-order held 111: 67:signal must be 45: 17: 12: 11: 5: 574: 564: 563: 558: 556:Linear filters 553: 537: 536: 525: 513: 502: 490: 466: 459: 421: 398: 386: 345: 344: 342: 339: 338: 337: 332: 325: 322: 321: 320: 315: 289: 286: 250:Lanczos window 242: 241: 231: 225: 214: 213:Common filters 211: 164: 161: 115:Dirac impulses 110: 109:Implementation 107: 63:: the sampled 44: 41: 15: 9: 6: 4: 3: 2: 573: 562: 559: 557: 554: 552: 549: 548: 546: 534: 529: 523:, Ron Bigelow 522: 517: 511: 506: 499: 494: 486: 482: 481: 473: 471: 462: 460:0-89791-275-6 456: 452: 448: 444: 437: 436: 428: 426: 414: 407: 405: 403: 395: 389: 387:1-58113-308-1 383: 379: 375: 371: 364: 363: 355: 353: 351: 346: 336: 333: 331: 328: 327: 319: 316: 314: 311: 310: 309: 307: 303: 299: 295: 285: 281: 279: 275: 271: 266: 262: 257: 255: 254:Kaiser window 251: 245: 239: 235: 232: 229: 226: 223: 220: 219: 218: 210: 208: 204: 203:gamma encoded 199: 195: 193: 192:interpolation 189: 184: 182: 178: 174: 170: 160: 157: 155: 154:audio filters 151: 146: 144: 139: 134: 132: 131:Nyquist limit 128: 124: 120: 116: 106: 104: 100: 96: 91: 89: 85: 80: 78: 74: 70: 66: 62: 59:, called the 58: 54: 50: 40: 38: 34: 30: 26: 22: 528: 516: 505: 493: 479: 434: 361: 291: 282: 258: 246: 243: 238:cubic spline 216: 200: 196: 185: 180: 166: 158: 147: 143:oversampling 135: 122: 112: 92: 83: 81: 76: 64: 46: 32: 28: 18: 71:to prevent 69:bandlimited 545:Categories 341:References 304:photos or 188:decimation 181:derivative 177:resampling 306:MRI scans 265:B-splines 123:or images 324:See also 278:roll-off 261:Gaussian 175:and for 77:recorded 73:aliasing 294:wavelet 25:digital 457:  384:  84:output 21:analog 439:(PDF) 416:(PDF) 366:(PDF) 302:X-ray 65:input 27:), a 455:ISBN 382:ISBN 252:and 207:sRGB 138:sinc 103:sinc 47:The 23:and 447:doi 374:doi 190:or 167:In 53:ADC 37:DAC 547:: 483:. 469:^ 453:. 441:. 424:^ 401:^ 380:. 368:. 349:^ 90:. 487:. 463:. 449:: 418:. 396:) 392:( 390:. 376::

Index

analog
digital
DAC
sampling theorem
ADC
electronic filter
anti-aliasing filter
bandlimited
aliasing
Whittaker–Shannon interpolation formula
brickwall filters
Nyquist frequency
sinc
Dirac impulses
zero-order held
image frequencies
Nyquist limit
sinc
oversampling
anti-aliasing filter
audio filters
image processing
medical imaging
resampling
decimation
interpolation
gamma encoded
sRGB
nearest-neighbor interpolation
bilinear interpolation

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