2011
DOI: 10.1080/01431161.2010.486011
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Deconvolution of MODIS imagery using multiscale maximum entropy

Abstract: A multiscale maximum entropy method (MEM) for image deconvolution is implemented and applied to MODIS (moderate resolution imaging spectroradiometer) data to remove instrument point-spread function (PSF) effects. The implementation utilizes three efficient computational methods: a fast Fourier transform convolution, a wavelet image decomposition and an algorithm for gradient method step-size estimation that together enable rapid image deconvolution. Multiscale entropy uses wavelet transforms to implicitly incl… Show more

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Cited by 7 publications
(4 citation statements)
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“…Although more sophisticated deconvolution algorithms exist [31,[44][45][46], they may rely on a higher level of mathematical understanding to implement. Without a fundamental understanding of a method, its implementation can lead to inaccurate interpretations.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…Although more sophisticated deconvolution algorithms exist [31,[44][45][46], they may rely on a higher level of mathematical understanding to implement. Without a fundamental understanding of a method, its implementation can lead to inaccurate interpretations.…”
Section: Discussionmentioning
confidence: 99%
“…With this in mind, if sensor blurring is the major obstacle for a particular application, the developed methodologies should be sufficient to observe noticeable improvements. From that point, more complex deconvolution algorithms (e.g., [31,[44][45][46]) can be implemented if the developed algorithm is introducing too many artifacts in the HSI data.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…As attention was focused on mapping water, which is relatively separable from land in the near-infrared part of the spectrum, and especially small lakes, a 250m spatial resolution image in the near infrared (841-876 nm) waveband was used. The MODIS imagery used was derived from tile 13 horizontal and 03 vertical of the MOD09GQ, a level 2 data, which have not been gridded into a map projection as in Level 3 data of composite images [35], facilitating further processing to be determined by users, such as relative shift measurement and reduction of sensor point spread function effects [36]. The MODIS images were projected from Sinusoidal projection into a Landsat Universal Transverse Mercator (UTM) projection at zone 16.…”
Section: Coarse Resolution Imagerymentioning
confidence: 99%