We present a novel approach to nonrigid registration of volumetric multimodal medical data. We propose a new regularized template matching scheme, where arbitrary similarity measures can be embedded and the regularization imposes spatial coherence taking into account the quality of the matching according to an estimation of the local structure. We propose to use an efficient variation of weighted least squares termed normalized convolution as a mathematically coherent framework for the whole approach. Results show that our method is fast as accurate.
SUMMARY: A methodology to obtain the sea surface temperature (SST) in the Canary-Azores-Gibraltar area has been developed. The final accuracy of the AVHRR-based SST retrievals depends both on the accuracy of the measured radiance and the accuracy of the SST retrieval algorithm that converts the measured radiance into sea surface temperature. The procedure made in this framework consists of: (i) a radiance-based non-linearity correction method; (ii) an automatic procedure for the geometric correction, achieving accuracy to the order of the pixel; (iii) an improved algorithm for cloud detection, based on the method of the multiband thresholds; (iv) a new split-window function (SWF) to perform atmospheric correction in CANIGO area. This task has been accomplished by using the matchup data set of AVHRR brightness temperature (channel 4 and 5) and in situ SST data. The matchups were carefully screened from the HRPT scenes of all seasons in 1996-1998. The temporal and spatial coincidences are within 30 minutes and one pixel resolution, respectively. Coefficients of that algorithm are estimated from regression analysis using 60 co-located in situ and satellite measurements (matchups). Error analysis has shown that SST can theoretically be retrieved to within 0.38ºC RMS.
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