Multi-resolution volume rendering is an effective method to solve the problem of massive data volume rendering. We assume that there are some homogeneous regions with smaller variance or Shannon entropy in the data. By reducing the resolution of these areas

the overall amount of data can be reduced. However

for some kind of data

such as seismic data

there are only few homogeneous regions. For such data

traditional methods can hardly achieve the goal of multi-resolution. In this paper

a target-based multi-resolution volume rendering method is proposed based on the traditional method. Its basic idea is to use the target feature of the data as a guide to find the target areas. In some cases

the Shannon entropy and variance can only reflect the numerical changes

but not the information

which is required by the users. Therefore

this method uses the target feature to find the target areas

which are of interest for the user. By appropriately reducing the resolution of non-target areas after processing the data in the traditional way the compression ratio is improved. This method can meet the demand of computer memory by reducing the amount of data for non-critical regions and to protect the data in target regions as far as possible. In this way

we can achieve multi-resolution volume rendering effectively without losing the critical information of target areas. Under the premise of guarantee the amount of data

this method can get a better rendering results by dropping the amount of information in the non-target area

and to ensure high drawing quality of the target region. Experimental results show that compared with traditional methods

the proposed method can get better drawing effects in critical areas

while further reducing the amount of data used to draw.