### Abstract

This paper presents a new approach for reconstructing object surface covered with 3D points. It utilizes the 2D Daubechies scaling functions of 3 ^{rd} order, which can describe fractal geometry, to formulate the observation equation for each point. The linear system is then solved by the least-squares adjustment (LSA) and the reconstructed surface can then be generated. To overcome the ill-posed problem which often emerges in LSA, we employ a from-coarse-to-fine strategy and use the pseudo observations designed on dyadic points, called PHO (Pseudo Height Observations) and POI (Pseudo Observations by Interpolation). Moreover, a full-automated weighting model is proposed to eliminate the so-called Gibbs effect. It reduces the weights of the points whose absolute residuals are larger than twice the a priori height accuracy of the LiDAR point. Tests are done by using airborne LiDAR points. They verify that the artifacts can be completely eliminated by adopting the pseudo observations and the weighting model. While the dyadic points have approximately the point interval of LiDAR points, the a posteriori standard deviations of unit weight of our tests are about ±20∼23cm which are all to the extents of the a priori height accuracy, ±25cm.

Original language | English |
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Title of host publication | Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006 |

Pages | 1130-1135 |

Number of pages | 6 |

Publication status | Published - 2006 Dec 1 |

Event | 27th Asian Conference on Remote Sensing, ACRS 2006 - Ulaanbaatar, Mongolia Duration: 2006 Oct 9 → 2006 Oct 13 |

### Publication series

Name | Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006 |
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### Other

Other | 27th Asian Conference on Remote Sensing, ACRS 2006 |
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Country | Mongolia |

City | Ulaanbaatar |

Period | 06-10-09 → 06-10-13 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Networks and Communications

### Cite this

*Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006*(pp. 1130-1135). (Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006).

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*Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006.*Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006, pp. 1130-1135, 27th Asian Conference on Remote Sensing, ACRS 2006, Ulaanbaatar, Mongolia, 06-10-09.

**A wavelet approach for determining a surface covered with airborne LiDAR points.** / Tsay, Jaan-Rong; Yen, Cheng Wei.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A wavelet approach for determining a surface covered with airborne LiDAR points

AU - Tsay, Jaan-Rong

AU - Yen, Cheng Wei

PY - 2006/12/1

Y1 - 2006/12/1

N2 - This paper presents a new approach for reconstructing object surface covered with 3D points. It utilizes the 2D Daubechies scaling functions of 3 rd order, which can describe fractal geometry, to formulate the observation equation for each point. The linear system is then solved by the least-squares adjustment (LSA) and the reconstructed surface can then be generated. To overcome the ill-posed problem which often emerges in LSA, we employ a from-coarse-to-fine strategy and use the pseudo observations designed on dyadic points, called PHO (Pseudo Height Observations) and POI (Pseudo Observations by Interpolation). Moreover, a full-automated weighting model is proposed to eliminate the so-called Gibbs effect. It reduces the weights of the points whose absolute residuals are larger than twice the a priori height accuracy of the LiDAR point. Tests are done by using airborne LiDAR points. They verify that the artifacts can be completely eliminated by adopting the pseudo observations and the weighting model. While the dyadic points have approximately the point interval of LiDAR points, the a posteriori standard deviations of unit weight of our tests are about ±20∼23cm which are all to the extents of the a priori height accuracy, ±25cm.

AB - This paper presents a new approach for reconstructing object surface covered with 3D points. It utilizes the 2D Daubechies scaling functions of 3 rd order, which can describe fractal geometry, to formulate the observation equation for each point. The linear system is then solved by the least-squares adjustment (LSA) and the reconstructed surface can then be generated. To overcome the ill-posed problem which often emerges in LSA, we employ a from-coarse-to-fine strategy and use the pseudo observations designed on dyadic points, called PHO (Pseudo Height Observations) and POI (Pseudo Observations by Interpolation). Moreover, a full-automated weighting model is proposed to eliminate the so-called Gibbs effect. It reduces the weights of the points whose absolute residuals are larger than twice the a priori height accuracy of the LiDAR point. Tests are done by using airborne LiDAR points. They verify that the artifacts can be completely eliminated by adopting the pseudo observations and the weighting model. While the dyadic points have approximately the point interval of LiDAR points, the a posteriori standard deviations of unit weight of our tests are about ±20∼23cm which are all to the extents of the a priori height accuracy, ±25cm.

UR - http://www.scopus.com/inward/record.url?scp=84865646781&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865646781&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781604231380

T3 - Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006

SP - 1130

EP - 1135

BT - Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006

ER -