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A fully automatic method is proposed to produce an enhanced image from a very noisy sequence consisting of a translating object over a background with a different translational motion. The method is based on averaging registered versions of the frames in which the object has been motion-compensated. Conventional techniques for displacement estimation are not adequate for these very noisy sequences, and thus a new strategy has been used, taking advantage of a simple model of the sequences. First, the local spatiotemporal spectrum is estimated through a bank of multidirectional, multiscale third-order Gaussian derivative filters, yielding a representation of the sequence that facilitates further processing and analysis tasks. Then, energy-related measurements describing the local texture and motion and easily extracted from this representation. These descriptors are used to segment the sequence according to a local joint measure of motion and texture. Once the object of interest has been segmented, its velocity is estimated applying the gradient constraint to the output of a directional bandpass filter for all pixels belonging to the object. Velocity estimates are then used to compensate the motion prior to the average. The results obtained with real sequences of moving ships taken under very noisy conditions are highly satisfactory, demonstrating the robustness and usefulness of the proposed method. © 2000 Society of Photo-Optical Instrumentation EngineersThis research has been supported by the Comisión Interministerial de Ciencia y Tecnología of Spain, grant TIC98-0925-C02-01.Peer Reviewe

Automatic enhancement of noisy image sequences through local spatiotemporal spectrum analysis