Image Sequence Retrieval for Forecasting Weather Radar Echo Pattern
نویسندگان
چکیده
A novel method is proposed to retrieve image sequences with the goal of forecasting complex and timevarying natural patterns. To that end, we introduce a framework called Memory-Based Forecasting; it provides forecast information based on the temporal development of past retrieved sequences. This paper targets the radar echo patterns in weather radar images, and aims to realize an image retrieval method that supports weather forecasters in predicting local precipitation. To characterize the radar echo patterns, an appearance-based representation of the echo pattern, and its velocity field are employed. Temporal texture features are introduced to represent local pattern features including non-rigid complex motion. Furthermore, the temporal development of a sequence is represented as paths in eigenspaces of the image features, and a normalized distance between two sequences in the eigenspace is proposed as a dissimilarity measure that is used in retrieving similar sequences. Several experiments confirm the good performance of the proposed retrieval scheme, and indicate the predictability of the image sequence. key words: image sequence retrieval, weather radar image, temporal texture, weather forecasting
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Memory-Based Forecasting for Weather Image Patterns
A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts’ decision making. This paper targets the local precipitation phenomena captured as echo patterns in weather radar images, and aims to realize a tool that supports weather forecasters. In our framework, past image patterns similar to...
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