Wavelet analysis and processing algorithm for large-scale image

Wavelet analysis, the newest time-frequency analysis tool with its unique advantages, was widely used in engineering. However, in the practical application, the huge size of the data made it difficult and impossible to process a Large-scale image by the ordinary wavelet process method. But Wavelet analysis still works well when the normal size image is processed. According to the facts mentioned before, we supposed that the batch treating data, distributional processing data, and the improvement wavelet algorithm might be the ways to solve Large-scale image's size problem. To prove our hypotheses' validity, we made a practical application contrasting the similar degree of the two large-scale images. Since we successfully get two images' error, we prove that one of our hypotheses-batch treating data is feasible and it is possible to use the wavelet analysis in the Large-scale image process.