The image classification is a key step for remote sensing data transforming into practical information and knowledge

which has always been the core problem in the remote sensing field.The limitations in traditional spectral classification method otherwise promotes the theory development on the spatial-spectral coupled information cognition of remote sensing

which focuses more on the spatial relationship.However

the current classification revision methods have configured the spatial forms and relationship while

going further

but there still exist some deficiencies in spatial distribution theorem about quantitative description

objects’ actual distribution

and so on.Thus

the paper proposes a spatial-adjacency-supported classification revision method inclusive of reference object extraction

target object pixels searching and reference adjacent objects distinguishing which detailed steps are:（1） marking the objects out and getting their distribution rangepicking up the other objects in the range

（2） selecting them as the target object

picking out the unavailable target object in the range and selecting them as a certain objectwhich also provides a convenient and effective way for stepwise and accurate extraction of other objects subsequently.We also carried out an experiment on offshore area classification revision

and the result proved to be more accurate and reasonable.