The paper discusses the application of Principle Component Analysis(PCA) in image’s feature attributes reduction. After PCA pre-processing

Rough Set theory was introduced

and its application in characterized parameters’ attribute optimization was also explored. The unnecessary attributeswere eliminated with an attribute reduction algorithm. The inner redundancy of CBIR was revealed. The result of attribute reduction using UCI dataset proved the algorithm can exclude the influence of unused attributes and decrease the complexity of CBIR effectively.