On Lifting Scheme For Multiwavelet Transforms And Cloud Image Coding

As analysis tool for time-frequency appeared at the end of 1980s, wavelet transform was extensively applied in the field of image coding. As compact, symmetrical, orthogonal and uncommon unit-wavelet does not exist in real number field, Goodman, etc. put forward the concept of multiwavelet. Multiwavelet keeps the excellent characteristics of time and frequency field owned by unit-wavelet and overcomes the defects of unit-wavelet. Multiwavelet combines smoothness, compactness, symmetry and orthogonality together perfectly, which is very important in actual practice. Because of its theoretical advantages and potentiality in the field of practice multiwavelet gained high attention. People are exploring actively its application in image processing and have made certain achievement in image coding and image noise reduction. As data are abundant it is necessary to compress image data for practical use. With the development of meteorological technology, weather stations, weather radar and meteorological satellites which spread all over the world provide a vast amount of information about weather situation everyday. Because the data are abundant in the course of storing and we have to pay high cost in transmission and store, it is necessary to compress the data by image coding technology.In this paper we make use of the advantages of wavelet analysis in image compression, estimation and reversion to compress the cloud image. Starting from the concept of error energy, using 2-dimension correlation coefficient we study the similarity of 2-dimension signal in space and give three judge methods of similarity of multi-image. Using these methods we can choose one from these multi-image, which reduces the amount of data that put into cloud image database in a sense and solves the problem of time redundancy of cloud image database. Using 2-dimension correlation coefficient and correlation function, we can find multiwavelet that is fit for compression coding of cloud image. As multiwavelet needs prefilter, and prefilter destroys many characteristics of multiwavelet, we use balance multiwavelet to improve the lifting scheme model, raise new methods of prefilter design in the model and use the improvedmodel to make compression coding of cloud image and computer simulation. The result shows that the improved model is superior to the original model.