The good spatial-frequencial localization characteristics of wavelet transform make the energy of image congregate mostly in lower frequency subimage. This paper utilizes the property of the asymmetrical energy distribution on different multiresolution levels

and introduces a method which is called multiresolution levels compression (MLC) to process the image on the levels of different multiresolution. By the estimate and studying of the quantization coefficients during wavelet transform on every decomposed level

the experiment can get the best quantization coefficient for any particular level. Theoretical analysis and experimental results demonstrate that a method of higher compression rate is implemented. In the experiment

the best quantization coefficient of every level is determined by the data analysis of human. For the aim to process huge amount of images such as the images from the Internet

the technology of artificial intelligence and machine learning can be used to let the computer use MLC method by studying a certain number of image examples and then process more images automatically. The ability to use the MLC method would also improve according to the amount of images the computer has studied. This is the new direction to perform in the near future.