Low Complexity Algorithm Suitable for Compressing High-resolution Aerial Image Data

In order to solve problem that the high-resolution aerial image data is greatness,a low complexity algorithm of image compression is proposed based on wavelet analysis in this paper.Firstly,the co relational redundancy between the image pixels is removed by the two-dimensional 5/3 wavelet transform of five levels to image data.Then visual redundancy is removed by the optimal quantitative to transform image coefficients according as sub-band transform gain of wavelet transform.Finally,by the characteristic of the probability distribution that the wavelet transform coefficients,the prediction entropy coding based on context for lowest frequency sub-band.For other band with Columbus index encoded joint adaptive run-length coding and using specifically scan.Experimental results show that the algorithm has the premise of the image compression quality get higher compression ratio,and supports coding from loss to lossless,and low complex,and it is very suitable for hardware implementation.