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Rosenfeld, A.

Publications and source records attributed to Rosenfeld, A..

15 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Image processing in remote sensing data analysis - The state of the art

Image analysis techniques applicable to remote sensing data and covering image models, feature detection, segmentation and classification, texture analysis, and matching are studied. Model types for characterizing images examined include random-field, mosaic, and facet models. Edge and corner detection as well as global extraction of linear features are discussed. Pixel clustering and classification are covered in addition to the regional approach to segmentation. Autocorrelation, second-order gray level probability density, and the use of primitive element statistics are discussed in relation to texture analysis. Finally, reducing the cost of (sub)imaging matching methods (e.g., pixelwise comparison of gray levels and normalized cross-correlation between two images) as well as improving match sharpness is considered.

Rosenfeld, A.↗
NASA NTRS1983

Image matching using Hough transforms

Image matching using Hough transforms is discussed. Known objects in imagery are used as input to the transforms which allow prediction of similar objects in the imagery.

Davis, L. S.↗
NASA NTRS1982

Shape and texture

Methods used to measure the geometrical properties of regions in a segmented image are discussed including the use of centroids, moments, and principle axes. In addition, statistical picture properties, particularly those which describe visual texture, are discussed. Gray level statistics, local property statistics, and autocorrelation and power spectrum are addressed.

Rosenfeld, A.↗
NASA NTRS1978

A Fourier approach to cloud motion estimation

A Fourier phase-difference technique for cloud motion estimation from pairs of pictures is described, and results obtained using this technique are compared with the results of a Fourier-domain cross-correlation scheme. The phase-difference technique makes use of the phase of the cross-spectral density and allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. When objects being tracked do not change their shape, size, and orientation to more than a limited degree, both techniques are effective. The phase difference technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects; in these circumstances, the cross-correlation scheme is preferable. It is suggested that the Fourier transform phase difference estimation methods can be applied in problems such as landmark matching.

Arking, A.↗
NASA NTRS1974

Fourier transform techniques for the inference of cloud motion

The development and evaluation are reported of phase shift techniques based on the Fourier transform for the estimation of cloud motion from geosynchronous meteorological satellite photographs. An alternative approach to cloud motion estimation, involving thresholding, was proposed and studied.

Lo, R. C.↗
NASA NTRS1974

Techniques for the processing of remotely sensed imagery

The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.

Deutsch, E. S.↗
NASA NTRS1974

Edge and line detection in ERTS imagery: A comparative study

Several local edge detection operators were applied to a set of ERTS pictures of the Monterey, Calif. area. Gradient operators performed consistently better than laplacian operators in detecting edges. It was also found that if a grayscale normalization operation, histogram flattening, was applied to the pictures first, the edge detector outputs were greatly enhanced. The use of interpolation for more accurate location of edges on a digital picture was also briefly investigated. Curve detection operators were applied to the edge detector outputs; this had the effect of enhancing the edges while suppressing noise.

Eberlein, R.↗
NASA NTRS1971

Automatic cloud cover mapping.

A method of converting a picture into a 'cartoon' or 'map' whose regions correspond to differently textured regions is described. Texture edges in the picture are detected, and solid regions surrounded by these (usually broken) edges are 'colored in' using a propagation process. The resulting map is cleaned by comparing the region colors with the textures of the corresponding regions in the picture, and also by merging some regions with others according to criteria based on topology and size. The method has been applied to the construction of cloud cover maps from cloud cover pictures obtained by satellites.

Strong, J. P., III↗