@inproceedings {199,
	title = {Despeckling vs averaging of retinal UHROCT tomograms: advantages and limitations},
	booktitle = {Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV},
	year = {2011},
	publisher = {SPIE},
	organization = {SPIE},
	abstract = {<p>Imaging time can be reduced using despeckled tomograms, which have similar image metrics to those obtained by averaging several low speed tomograms or many high speed tomograms. Quantitative analysis was used to compare the performance of two speckle denoising approaches, algorithmic despeckling and frame averaging, as applied to retinal OCT images. Human retinal tomograms were acquired from healthy subjects with a research grade 1060nm spectral domain UHROCT system with 5μm axial resolution in the retina. Single cross-sectional retinal tomograms were processed with a novel speckle denoising algorithm and compared with frame averaged retinal images acquired at the same location. Image quality metrics such as the image SNR and contrast-to-noise ratio (CNR) were evaluated for both cases.</p>
},
	keywords = {biomedical optics, image processing, medical imaging, optical coherence tomography, speckle},
	doi = {http://dx.doi.org/10.1117/12.875867},
	url = {http://link.aip.org/link/?PSI/7889/78893C/1},
	author = {D D. Lee and K Bizheva and A Wong and J A. Eichel and P Fieguth and D A. Clausi},
	editor = {J A. Izatt and J G. Fujimoto and V V. Tuchin}
}
@article {575,
	title = {The effect of speckle filtering on scale-dependent texture estimation of a forested scene},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {38},
	year = {2000},
	pages = {1160 - 1170},
	abstract = {<p>Spatial fluctuations in microwave backscatter may be an important piece of information in discriminating tree stands. However, the presence of speckle in synthetic aperture radar (SAR) image data is a barrier to the exploitation of image texture. The authors explored a new methodology that combines a recent adaptive speckle reduction algorithm by Lopes et al. (1990) with a generic texture estimation scheme. They investigated the claim that this filter was capable of preserving backscatter texture. To understand if speckle reduction was destroying backscatter texture, they compared the strength of the relationship between forest inventory parameters and image texture as a function of spatial scale for both filtered and unfiltered images. They used Radarsat Fine mode image data: single look resolution is approximately 8.5 m, and pixel spacing is 3 m. Their study area was northern Vancouver Island, B.C., on the west coast of Canada. For the unfiltered data, they found that the ability of image texture to predict the forest parameters decreased as the texture scale increased from 3 to 13 m, suggesting greater information content in the small scale texture. For the filtered data, this relationship was much weaker at small scales and was not a function of distance. Their results suggest that the speckle filter was not retaining small scale texture, which is consistent with the theoretical hypotheses underlying its multiplicative noise model. They also show that there is significant information in small state SAR image texture that may be used as an adjunct to other spatial information for discriminating tree stands in the temperate rain forest</p>
},
	keywords = {adaptive signal processing, adaptive speckle reduction algorithm, backscatter texture, forest, forested scene, forestry, generic texture estimation scheme, geophysical measurement technique, geophysical signal processing, geophysical techniques, image texture, land surface, microwave backscatter, radar imaging, radar remote sensing, remote sensing by radar, SAR, scale-dependent texture estimation, spatial fluctuations, speckle, speckle filtering, synthetic aperture radar, tree stand, vegetation mapping},
	issn = {0196-2892},
	author = {M J. Collins and J Wiebe and D A. Clausi}
}
